Encoder, decoder, encoding method, and decoding method

ABSTRACT

An encoder encodes a video, and includes: circuitry; and memory coupled to the circuitry. Using the memory, the circuitry: obtains at least two items of prediction information for a first partition included in the video; derives at least one template from neighboring samples which neighbor the first partition; calculates at least two costs, using the at least one template and the at least two items of prediction information; using the at least two costs, (i) determines at least one splitting direction for the first partition or (ii) assigns one of the at least two items of prediction information to a second partition split from the first partition according to the splitting direction, and another thereof to a third partition split from the first partition according to the splitting direction; and encodes the first partition according to the splitting direction and the at least two items of prediction information.

FIELD

The present disclosure relates to, for instance, an encoder whichencodes videos.

BACKGROUND

H.265 also referred to as high efficiency video coding (HEVC) is present(Non-patent Literature (NPL) 1) as a conventional video encodingstandard.

CITATION LIST Non-Patent Literature

[NPL 1] H.265 (ISO/IEC 23008-2 HEVC)/HEVC (High Efficiency Video Coding)

SUMMARY Technical Problem

However, it is not easy to adaptively determine information related tosplitting based on characteristics of neighboring samples in, forinstance, video encoding, while inhibiting an increase in the amount ofprocessing.

In view of this, non-limiting and exemplary embodiments provide anencoder which can adaptively determine information related to splitting,based on characteristics of neighboring samples, while inhibiting anincrease in the amount of processing.

Solution to Problem

An encoder according to an aspect of the present disclosure is anencoder which encodes a video, the encoder including: circuitry; andmemory coupled to the circuitry. Using the memory, the circuitry:obtains at least two items of prediction information for a firstpartition included in the video; derives at least one template from aplurality of neighboring samples which neighbor the first partition;calculates at least two costs, using the at least one template and theat least two items of prediction information; using the at least twocosts, (i) determines at least one splitting direction for the firstpartition or (ii) assigns one of the at least two items of predictioninformation to a second partition split from the first partitionaccording to the at least one splitting direction, and another of the atleast two items of prediction information to a third partition splitfrom the first partition according to the at least one splittingdirection; and encodes the first partition according to the at least onesplitting direction and the at least two items of predictioninformation.

Note that these general and specific aspects may be implemented using asystem, a device, a method, an integrated circuit, a computer program,or a non-transitory computer-readable recording medium such as a CD-ROM,or any combination of systems, devices, methods, integrated circuits,computer programs, or computer-readable recording media.

Additional benefits and advantages of the disclosed embodiments will beapparent from the specification and the drawings. The benefits and/oradvantages may be individually obtained by various embodiments andfeatures of the specification and the drawings which need not be allprovided in order to obtain one or more of the benefits and/oradvantages.

Advantageous Effects

An encoder according to an aspect of the present disclosure canadaptively determine information related to splitting based oncharacteristics of neighboring samples, while inhibiting an increase inthe amount of processing.

BRIEF DESCRIPTION OF DRAWINGS

These and other objects, advantages and features of the disclosure willbecome apparent from the following description thereof taken inconjunction with the accompanying drawings that illustrate a specificembodiment of the present disclosure.

FIG. 1 is a block diagram illustrating a functional configuration of anencoder according to Embodiment 1.

FIG. 2 illustrates one example of block splitting according toEmbodiment 1.

FIG. 3 is a chart indicating transform basis functions for eachtransform type.

FIG. 4A illustrates one example of a filter shape used in ALF.

FIG. 4B illustrates another example of a filter shape used in ALF.

FIG. 4C illustrates another example of a filter shape used in ALF.

FIG. 5A illustrates 67 intra prediction modes used in intra prediction.

FIG. 5B is a flow chart for illustrating an outline of a predictionimage correction process performed via OBMC processing.

FIG. 5C is a conceptual diagram for illustrating an outline of aprediction image correction process performed via OBMC processing.

FIG. 5D illustrates one example of FRUC.

FIG. 6 is for illustrating pattern matching (bilateral matching) betweentwo blocks along a motion trajectory.

FIG. 7 is for illustrating pattern matching (template matching) betweena template in the current picture and a block in a reference picture.

FIG. 8 is for illustrating a model assuming uniform linear motion.

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks.

FIG. 9B is for illustrating an outline of a process for deriving amotion vector via merge mode.

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing.

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing.

FIG. 10 is a block diagram illustrating a functional configuration of adecoder according to Embodiment 1.

FIG. 11 is a flowchart illustrating an example of inter predictionprocessing according to a first aspect.

FIG. 12 illustrates examples of a second partition and a third partitionin the first aspect.

FIG. 13 illustrates examples of cost calculation in the first aspect.

FIG. 14 illustrates examples of processing in step S1003 in FIG. 11 .

FIG. 15 illustrates other examples of processing in step S1003 in FIG.11 .

FIG. 16 illustrates examples of parameters in the first aspect.

FIG. 17 is a flowchart illustrating an example of intra predictionprocessing in the first aspect.

FIG. 18 is a flowchart illustrating an example of inter predictionprocessing in a second aspect.

FIG. 19 illustrates examples of processing in step S3004 in FIG. 18 .

FIG. 20 illustrates other examples of processing in step S3004 in FIG.18 .

FIG. 21 illustrates examples of parameters in the second aspect.

FIG. 22 is a flowchart illustrating an example of intra predictionprocessing in the second aspect.

FIG. 23 is a flowchart illustrating an example of inter predictionprocessing when the first aspect and the second aspect are combined.

FIG. 24 illustrates examples of processing in steps S5003 and S5004 inFIG. 23 .

FIG. 25 illustrates other examples of processing in steps S5003 andS5004 in FIG. 23 .

FIG. 26 illustrates examples of parameters when the first aspect and thesecond aspect are combined.

FIG. 27 is a flowchart illustrating examples of intra predictionprocessing when the first aspect and the second aspect are combined.

FIG. 28 is a flowchart illustrating an example of inter predictionprocessing in a third aspect.

FIG. 29 illustrates an example of a second partition in the thirdaspect.

FIG. 30 illustrates examples of cost calculation in the third aspect.

FIG. 31 illustrates examples of processing in steps S7005 and S7006 inFIG. 28 .

FIG. 32 illustrates other examples of processing in steps S7005 andS7006 in FIG. 28 .

FIG. 33 illustrates an example of inter prediction processing to whichthe third aspect is not applied.

FIG. 34 illustrates an example of inter prediction processing to whichthe third aspect is applied.

FIG. 35 is a flowchart illustrating an example of inter predictionprocessing in a fourth aspect.

FIG. 36 illustrates an example of obtaining prediction partitions for afirst partition using a first motion vector.

FIG. 37 illustrates an example of obtaining prediction partitions forthe first partition using a second motion vector.

FIG. 38A illustrates examples of cost calculation in the fourth aspect.

FIG. 38B illustrates other examples of cost calculation in the fourthaspect.

FIG. 39A illustrates examples of processing in steps S8003 and S8004 inFIG. 35 .

FIG. 39B illustrates other examples of processing in steps S8003 andS8004 in FIG. 35 .

FIG. 40 is a block diagram illustrating an example of implementation ofan encoder according to Embodiment 1.

FIG. 41 is a block diagram illustrating an example of implementation ofa decoder according to Embodiment 1.

FIG. 42 illustrates an overall configuration of a content providingsystem for implementing a content distribution service.

FIG. 43 illustrates one example of an encoding structure in scalableencoding.

FIG. 44 illustrates one example of an encoding structure in scalableencoding.

FIG. 45 illustrates an example of a display screen of a web page.

FIG. 46 illustrates an example of a display screen of a web page.

FIG. 47 illustrates one example of a smartphone.

FIG. 48 is a block diagram illustrating a configuration example of asmartphone.

DESCRIPTION OF EMBODIMENTS Outline of Aspects of the Present Disclosure

For example, an encoder according to an aspect of the present disclosureis an encoder which encodes a video, the encoder including: circuitry;and memory coupled to the circuitry. Using the memory, the circuitry:obtains at least two items of prediction information for a firstpartition included in the video; derives at least one template from aplurality of neighboring samples which neighbor the first partition;calculates at least two costs, using the at least one template and theat least two items of prediction information; using the at least twocosts, (i) determines at least one splitting direction for the firstpartition or (ii) assigns one of the at least two items of predictioninformation to a second partition split from the first partitionaccording to the at least one splitting direction, and another of the atleast two items of prediction information to a third partition splitfrom the first partition according to the at least one splittingdirection; and encodes the first partition according to the at least onesplitting direction and the at least two items of predictioninformation.

Accordingly, based on characteristics of neighboring samples, theencoder can adaptively determine a splitting direction or assignprediction information to the split partitions. Thus, the encoder canadaptively determine information related to splitting, based oncharacteristics of neighboring samples. In addition, neighboring samplescan be used by the same method in video encoding processing and videodecoding processing. Accordingly, the encoder does not need to encodeinformation adaptively determined. Thus, the encoding amount can bereduced.

For example, the at least two items of prediction information are motionvectors.

Accordingly, the encoder can appropriately calculate costs for use indetermining information related to splitting, using the motion vectors.

For example, the at least two items of prediction information are mergecandidates.

Accordingly, the encoder can appropriately calculate costs for use indetermining information related to splitting, using the mergecandidates.

For example, the at least two items of prediction information are intraprediction modes.

Accordingly, the encoder can appropriately calculate costs for use indetermining information related to splitting, using the intra predictionmodes.

For example, the at least one template includes a template derived froman upper neighboring sample located above the first partition, among theplurality of neighboring samples.

Accordingly, the encoder can adaptively determine information related tosplitting, based on characteristics of the upper neighboring sample.

For example, the at least one template includes a template derived froma left neighboring sample located on a left of the first partition,among the plurality of neighboring samples.

Accordingly, the encoder can adaptively determine information related tosplitting, based on characteristics of the left neighboring sample.

For example, the at least one template includes a template derived froman upper neighboring sample located above the first partition, and atemplate derived from a left neighboring sample located on a left of thefirst partition, among the plurality of neighboring samples.

Accordingly, the encoder can adaptively determine information related tosplitting, based on characteristics of the upper neighboring sample andcharacteristics of the left neighboring sample.

For example, calculation of the at least two costs includes at least aminus operation.

Accordingly, the encoder can appropriately calculate costs, based on theminus operation.

For example, the second partition and the third partition are triangularpartitions.

Accordingly, the encoder can adaptively determine information associatedwith splitting a partition into two triangular partitions, based oncharacteristics of neighboring samples.

For example, the second partition and the third partition arerectangular partitions.

Accordingly, the encoder can adaptively determine information associatedwith splitting a partition into two rectangular partitions, based oncharacteristics of neighboring samples.

For example, the at least one splitting direction is a direction from atop-left corner to a bottom-right corner of the first partition or adirection from a top-right corner to a bottom-left corner of the firstpartition.

Accordingly, the encoder can adaptively determine information related tosplitting in an oblique direction, based on characteristics ofneighboring samples.

For example, the at least one splitting direction is horizontal orvertical.

Accordingly, the encoder can adaptively determine information related tosplitting in the horizontal direction or the vertical direction, basedon characteristics of neighboring samples.

For example, the at least two items of prediction information includefirst prediction information and second prediction information differentfrom the first prediction information, and the first predictioninformation and the second prediction information are obtained for thesecond partition and the third partition in the first partition,respectively.

Accordingly, the encoder can appropriately determine information relatedto splitting, using the first prediction information for the secondpartition and the second prediction information for the third partition.

For example, using the at least two costs, the circuitry (i) determinesat least one splitting direction for the first partition, and (ii)assigns one of the at least two items of prediction information to thesecond partition, and another of the at least two items of predictioninformation to the third partition.

Accordingly, the encoder can adaptively perform both determination of asplitting direction and assignment of prediction information, based oncharacteristics of neighboring samples.

For example, the at least two costs are calculated using at least twoprediction partitions predicted from at least two reference frames ofthe first partition using the at least two items of predictioninformation.

Accordingly, the encoder can appropriately calculate costs using theprediction partitions.

For example, a decoder according to an aspect of the present disclosureis a decoder which decodes a video, the decoder including: circuitry;and memory coupled to the circuitry. Using the memory, the circuitry:obtains at least two items of prediction information for a firstpartition included in the video; derives at least one template from aplurality of neighboring samples which neighbor the first partition;calculates at least two costs, using the at least one template and theat least two items of prediction information; using the at least twocosts, (i) determines at least one splitting direction for the firstpartition or (ii) assigns one of the at least two items of predictioninformation to a second partition split from the first partitionaccording to the at least one splitting direction, and another of the atleast two items of prediction information to a third partition splitfrom the first partition according to the at least one splittingdirection; and decodes the first partition according to the at least onesplitting direction and the at least two items of predictioninformation.

Accordingly, the decoder can adaptively determine a splitting directionor assign prediction information to the split partitions, based oncharacteristics of neighboring samples. Thus, the decoder can adaptivelydetermine information related to splitting, based on characteristics ofneighboring samples. The neighboring samples can be used by the samemethod in video encoding processing and video decoding processing.Accordingly, the decoder does not need to decode information determinedadaptively. Accordingly, the encoding amount can be reduced.

For example, the at least two items of prediction information are motionvectors.

Accordingly, the decoder can appropriately calculate costs for use indetermining information related to splitting, using the motion vectors.

For example, the at least two items of prediction information are mergecandidates.

Accordingly, the decoder can appropriately calculate costs for use indetermining information related to splitting, using the mergecandidates.

For example, the at least two items of prediction information are intraprediction modes.

Accordingly, the encoder can appropriately calculate costs for use indetermining information related to splitting, using the intra predictionmodes.

For example, the at least one template includes a template derived froman upper neighboring sample located above the first partition, among theplurality of neighboring samples.

Accordingly, the encoder can adaptively determine information related tosplitting, based on characteristics of the upper neighboring sample.

For example, the at least one template includes a template derived froma left neighboring sample located on a left of the first partition,among the plurality of neighboring samples.

Accordingly, the encoder can adaptively determine information related tosplitting, based on characteristics of the left neighboring sample.

For example, the at least one template includes a template derived froman upper neighboring sample located above the first partition, and atemplate derived from a left neighboring sample located on a left of thefirst partition, among the plurality of neighboring samples.

Accordingly, the encoder can adaptively determine information related tosplitting, based on characteristics of the upper neighboring sample andcharacteristics of the left neighboring sample.

For example, calculation of the at least two costs includes at least aminus operation.

Accordingly, the encoder can appropriately calculate costs, based on theminus operation.

For example, the second partition and the third partition are triangularpartitions.

Accordingly, the encoder can adaptively determine information associatedwith splitting a partition into two triangular partitions, based oncharacteristics of neighboring samples.

For example, the second partition and the third partition arerectangular partitions.

Accordingly, the encoder can adaptively determine information associatedwith splitting a partition into two rectangular partitions, based oncharacteristics of neighboring samples.

For example, the at least one splitting direction is a direction from atop-left corner to a bottom-right corner of the first partition or adirection from a top-right corner to a bottom-left corner of the firstpartition.

Accordingly, the encoder can adaptively determine information related tosplitting in an oblique direction, based on characteristics ofneighboring samples.

For example, the at least one splitting direction is horizontal orvertical.

Accordingly, the encoder can adaptively determine information related tosplitting in the horizontal direction or the vertical direction, basedon characteristics of neighboring samples.

For example, the at least two items of prediction information includefirst prediction information and second prediction information differentfrom the first prediction information, and the first predictioninformation and the second prediction information are obtained for thesecond partition and the third partition in the first partition,respectively.

Accordingly, the encoder can appropriately determine information relatedto splitting, using the first prediction information for the secondpartition and the second prediction information for the third partition.

For example, using the at least two costs, the circuitry (i) determinesat least one splitting direction for the first partition, and (ii)assigns one of the at least two items of prediction information to thesecond partition, and another of the at least two items of predictioninformation to the third partition.

Accordingly, the encoder can adaptively perform both determination of asplitting direction and assignment of prediction information, based oncharacteristics of neighboring samples.

For example, the at least two costs are calculated using at least twoprediction partitions predicted from at least two reference frames ofthe first partition using the at least two items of predictioninformation.

Accordingly, the encoder can appropriately calculate costs, using theprediction partitions.

For example, an encoding method according to an aspect of the presentdisclosure is an encoding method for encoding a video, the encodingmethod including: obtaining at least two items of prediction informationfor a first partition included in the video; deriving at least onetemplate from a plurality of neighboring samples which neighbor thefirst partition; calculating at least two costs, using the at least onetemplate and the at least two items of prediction information; (i)determining at least one splitting direction for the first partition,using the at least two costs or (ii) assigning, using the at least twocosts, one of the at least two items of prediction information to asecond partition split from the first partition according to the atleast one splitting direction, and another of the at least two items ofprediction information to a third partition split from the firstpartition according to the at least one splitting direction; andencoding the first partition according to the at least one splittingdirection and the at least two items of prediction information.

Accordingly, based on characteristics of neighboring samples, thesplitting direction can be adaptively determined or predictioninformation can be adaptively assigned to the split partitions.Accordingly, information related to splitting can be adaptivelydetermined, based on characteristics of neighboring samples. Inaddition, neighboring samples can be used by the same method in videoencoding processing and video decoding processing. Accordingly,information adaptively determined does not need to be encoded. Thus, theencoding amount can be reduced.

For example, a decoding method according to an aspect of the presentdisclosure is a decoding method for decoding a video, the decodingmethod including: obtaining at least two items of prediction informationfor a first partition included in the video; deriving at least onetemplate from a plurality of neighboring samples which neighbor thefirst partition; calculating at least two costs, using the at least onetemplate and the at least two items of prediction information; (i)determining at least one splitting direction for the first partition,using the at least two costs or (ii) assigning, using the at least twocosts, one of the at least two items of prediction information to asecond partition split from the first partition according to the atleast one splitting direction, and another of the at least two items ofprediction information to a third partition split from the firstpartition according to the at least one splitting direction; anddecoding the first partition according to the at least one splittingdirection and the at least two items of prediction information.

Accordingly, based on characteristics of neighboring samples, thesplitting direction can be adaptively determined or predictioninformation can be adaptively assigned to the split partitions.Accordingly, information related to splitting can be adaptivelydetermined, based on characteristics of neighboring samples. Inaddition, neighboring samples can be used by the same method in videoencoding processing and video decoding processing. Accordingly,information adaptively determined does not need to be decoded. Thus, theencoding amount can be reduced.

Furthermore, these general and specific aspects may be implemented usinga system, a device, a method, an integrated circuit, a computer program,a computer-readable non-transitory recording medium such as a CD-ROM, orany combination of systems, devices, methods, integrated circuits,computer programs, or recording media.

Hereinafter, embodiments will be described with reference to thedrawings.

Note that the embodiments described below each show a general orspecific example. The numerical values, shapes, materials, components,the arrangement and connection of the components, steps, order of thesteps, etc., indicated in the following embodiments are mere examples,and therefore are not intended to limit the scope of the claims.Therefore, among the components in the following embodiments, those notrecited in any of the independent claims defining the broadest inventiveconcepts are described as optional components.

Embodiment 1

First, an outline of Embodiment 1 will be presented. Embodiment 1 is oneexample of an encoder and a decoder to which the processes and/orconfigurations presented in subsequent description of aspects of thepresent disclosure are applicable. Note that Embodiment 1 is merely oneexample of an encoder and a decoder to which the processes and/orconfigurations presented in the description of aspects of the presentdisclosure are applicable. The processes and/or configurations presentedin the description of aspects of the present disclosure can also beimplemented in an encoder and a decoder different from those accordingto Embodiment 1.

When the processes and/or configurations presented in the description ofaspects of the present disclosure are applied to Embodiment 1, forexample, any of the following may be performed.

-   (1) regarding the encoder or the decoder according to Embodiment 1,    among components included in the encoder or the decoder according to    Embodiment 1, substituting a component corresponding to a component    presented in the description of aspects of the present disclosure    with a component presented in the description of aspects of the    present disclosure;-   (2) regarding the encoder or the decoder according to Embodiment 1,    implementing discretionary changes to functions or implemented    processes performed by one or more components included in the    encoder or the decoder according to Embodiment 1, such as addition,    substitution, or removal, etc., of such functions or implemented    processes, then substituting a component corresponding to a    component presented in the description of aspects of the present    disclosure with a component presented in the description of aspects    of the present disclosure;-   (3) regarding the method implemented by the encoder or the decoder    according to Embodiment 1, implementing discretionary changes such    as addition of processes and/or substitution, removal of one or more    of the processes included in the method, and then substituting a    processes corresponding to a process presented in the description of    aspects of the present disclosure with a process presented in the    description of aspects of the present disclosure;-   (4) combining one or more components included in the encoder or the    decoder according to Embodiment 1 with a component presented in the    description of aspects of the present disclosure, a component    including one or more functions included in a component presented in    the description of aspects of the present disclosure, or a component    that implements one or more processes implemented by a component    presented in the description of aspects of the present disclosure;-   (5) combining a component including one or more functions included    in one or more components included in the encoder or the decoder    according to Embodiment 1, or a component that implements one or    more processes implemented by one or more components included in the    encoder or the decoder according to Embodiment 1 with a component    presented in the description of aspects of the present disclosure, a    component including one or more functions included in a component    presented in the description of aspects of the present disclosure,    or a component that implements one or more processes implemented by    a component presented in the description of aspects of the present    disclosure;-   (6) regarding the method implemented by the encoder or the decoder    according to Embodiment 1, among processes included in the method,    substituting a process corresponding to a process presented in the    description of aspects of the present disclosure with a process    presented in the description of aspects of the present disclosure;    and-   (7) combining one or more processes included in the method    implemented by the encoder or the decoder according to Embodiment 1    with a process presented in the description of aspects of the    present disclosure.

Note that the implementation of the processes and/or configurationspresented in the description of aspects of the present disclosure is notlimited to the above examples. For example, the processes and/orconfigurations presented in the description of aspects of the presentdisclosure may be implemented in a device used for a purpose differentfrom the moving picture/picture encoder or the moving picture/picturedecoder disclosed in Embodiment 1. Moreover, the processes and/orconfigurations presented in the description of aspects of the presentdisclosure may be independently implemented. Moreover, processes and/orconfigurations described in different aspects may be combined.

Encoder Outline

First, the encoder according to Embodiment 1 will be outlined. FIG. 1 isa block diagram illustrating a functional configuration of encoder 100according to Embodiment 1. Encoder 100 is a moving picture/pictureencoder that encodes a moving picture/picture block by block.

As illustrated in FIG. 1 , encoder 100 is a device that encodes apicture block by block, and includes splitter 102, subtractor 104,transformer 106, quantizer 108, entropy encoder 110, inverse quantizer112, inverse transformer 114, adder 116, block memory 118, loop filter120, frame memory 122, intra predictor 124, inter predictor 126, andprediction controller 128.

Encoder 100 is realized as, for example, a generic processor and memory.In this case, when a software program stored in the memory is executedby the processor, the processor functions as splitter 102, subtractor104, transformer 106, quantizer 108, entropy encoder 110, inversequantizer 112, inverse transformer 114, adder 116, loop filter 120,intra predictor 124, inter predictor 126, and prediction controller 128.Alternatively, encoder 100 may be realized as one or more dedicatedelectronic circuits corresponding to splitter 102, subtractor 104,transformer 106, quantizer 108, entropy encoder 110, inverse quantizer112, inverse transformer 114, adder 116, loop filter 120, intrapredictor 124, inter predictor 126, and prediction controller 128.

Hereinafter, each component included in encoder 100 will be described.

Splitter

Splitter 102 splits each picture included in an input moving pictureinto blocks, and outputs each block to subtractor 104. For example,splitter 102 first splits a picture into blocks of a fixed size (forexample, 128×128). The fixed size block is also referred to as codingtree unit (CTU). Splitter 102 then splits each fixed size block intoblocks of variable sizes (for example, 64×64 or smaller), based onrecursive quadtree and/or binary tree block splitting. The variable sizeblock is also referred to as a coding unit (CU), a prediction unit (PU),or a transform unit (TU). Note that in this embodiment, there is no needto differentiate between CU, PU, and TU; all or some of the blocks in apicture may be processed per CU, PU, or TU.

FIG. 2 illustrates one example of block splitting according toEmbodiment 1. In FIG. 2 , the solid lines represent block boundaries ofblocks split by quadtree block splitting, and the dashed lines representblock boundaries of blocks split by binary tree block splitting.

Here, block 10 is a square 128×128 pixel block (128×128 block). This128×128 block 10 is first split into four square 64×64 blocks (quadtreeblock splitting).

The top left 64×64 block is further vertically split into two rectangle32×64 blocks, and the left 32×64 block is further vertically split intotwo rectangle 16×64 blocks (binary tree block splitting). As a result,the top left 64×64 block is split into two 16×64 blocks 11 and 12 andone 32×64 block 13.

The top right 64×64 block is horizontally split into two rectangle 64×32blocks 14 and 15 (binary tree block splitting).

The bottom left 64×64 block is first split into four square 32×32 blocks(quadtree block splitting). The top left block and the bottom rightblock among the four 32×32 blocks are further split. The top left 32×32block is vertically split into two rectangle 16×32 blocks, and the right16×32 block is further horizontally split into two 16×16 blocks (binarytree block splitting). The bottom right 32×32 block is horizontallysplit into two 32×16 blocks (binary tree block splitting). As a result,the bottom left 64×64 block is split into 16×32 block 16, two 16×16blocks 17 and 18, two 32×32 blocks 19 and 20, and two 32×16 blocks 21and 22.

The bottom right 64×64 block 23 is not split.

As described above, in FIG. 2 , block 10 is split into 13 variable sizeblocks 11 through 23 based on recursive quadtree and binary tree blocksplitting. This type of splitting is also referred to as quadtree plusbinary tree (QTBT) splitting.

Note that in FIG. 2 , one block is split into four or two blocks(quadtree or binary tree block splitting), but splitting is not limitedto this example. For example, one block may be split into three blocks(ternary block splitting). Splitting including such ternary blocksplitting is also referred to as multi-type tree (MBT) splitting.

Subtractor

Subtractor 104 subtracts a prediction signal (prediction sample) from anoriginal signal (original sample) per block split by splitter 102. Inother words, subtractor 104 calculates prediction errors (also referredto as residuals) of a block to be encoded (hereinafter referred to as acurrent block). Subtractor 104 then outputs the calculated predictionerrors to transformer 106.

The original signal is a signal input into encoder 100, and is a signalrepresenting an image for each picture included in a moving picture (forexample, a luma signal and two chroma signals). Hereinafter, a signalrepresenting an image is also referred to as a sample.

Transformer

Transformer 106 transforms spatial domain prediction errors intofrequency domain transform coefficients, and outputs the transformcoefficients to quantizer 108. More specifically, transformer 106applies, for example, a predefined discrete cosine transform (DCT) ordiscrete sine transform (DST) to spatial domain prediction errors.

Note that transformer 106 may adaptively select a transform type fromamong a plurality of transform types, and transform prediction errorsinto transform coefficients by using a transform basis functioncorresponding to the selected transform type. This sort of transform isalso referred to as explicit multiple core transform (EMT) or adaptivemultiple transform (AMT).

The transform types include, for example, DCT-II, DCT-V, DCT-VIII,DST-I, and DST-VII. FIG. 3 is a chart indicating transform basisfunctions for each transform type. In FIG. 3 , N indicates the number ofinput pixels. For example, selection of a transform type from among theplurality of transform types may depend on the prediction type (intraprediction and inter prediction), and may depend on intra predictionmode.

Information indicating whether to apply such EMT or AMT (referred to as,for example, an AMT flag) and information indicating the selectedtransform type is signalled at the CU level. Note that the signaling ofsuch information need not be performed at the CU level, and may beperformed at another level (for example, at the sequence level, picturelevel, slice level, tile level, or CTU level).

Moreover, transformer 106 may apply a secondary transform to thetransform coefficients (transform result). Such a secondary transform isalso referred to as adaptive secondary transform (AST) or non-separablesecondary transform (NSST). For example, transformer 106 applies asecondary transform to each sub-block (for example, each 4×4 sub-block)included in the block of the transform coefficients corresponding to theintra prediction errors. Information indicating whether to apply NSSTand information related to the transform matrix used in NSST aresignalled at the CU level. Note that the signaling of such informationneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, or CTU level).

Here, a separable transform is a method in which a transform isperformed a plurality of times by separately performing a transform foreach direction according to the number of dimensions input. Anon-separable transform is a method of performing a collective transformin which two or more dimensions in a multidimensional input arecollectively regarded as a single dimension.

In one example of a non-separable transform, when the input is a 4×4block, the 4×4 block is regarded as a single array including 16components, and the transform applies a 16×16 transform matrix to thearray.

Moreover, similar to above, after an input 4×4 block is regarded as asingle array including 16 components, a transform that performs aplurality of Givens rotations on the array (i.e., a Hypercube-GivensTransform) is also one example of a non-separable transform.

Quantizer

Quantizer 108 quantizes the transform coefficients output fromtransformer 106. More specifically, quantizer 108 scans, in apredetermined scanning order, the transform coefficients of the currentblock, and quantizes the scanned transform coefficients based onquantization parameters (QP) corresponding to the transformcoefficients. Quantizer 108 then outputs the quantized transformcoefficients (hereinafter referred to as quantized coefficients) of thecurrent block to entropy encoder 110 and inverse quantizer 112.

A predetermined order is an order for quantizing/inverse quantizingtransform coefficients. For example, a predetermined scanning order isdefined as ascending order of frequency (from low to high frequency) ordescending order of frequency (from high to low frequency).

A quantization parameter is a parameter defining a quantization stepsize (quantization width). For example, if the value of the quantizationparameter increases, the quantization step size also increases. In otherwords, if the value of the quantization parameter increases, thequantization error increases.

Entropy Encoder

Entropy encoder 110 generates an encoded signal (encoded bitstream) byvariable length encoding quantized coefficients, which are inputs fromquantizer 108. More specifically, entropy encoder 110, for example,binarizes quantized coefficients and arithmetic encodes the binarysignal.

Inverse Quantizer

Inverse quantizer 112 inverse quantizes quantized coefficients, whichare inputs from quantizer 108. More specifically, inverse quantizer 112inverse quantizes, in a predetermined scanning order, quantizedcoefficients of the current block. Inverse quantizer 112 then outputsthe inverse quantized transform coefficients of the current block toinverse transformer 114.

Inverse Transformer

Inverse transformer 114 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 112. More specifically, inverse transformer 114 restores theprediction errors of the current block by applying an inverse transformcorresponding to the transform applied by transformer 106 on thetransform coefficients. Inverse transformer 114 then outputs therestored prediction errors to adder 116.

Note that since information is lost in quantization, the restoredprediction errors do not match the prediction errors calculated bysubtractor 104. In other words, the restored prediction errors includequantization errors.

Adder

Adder 116 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 114, and prediction samples,which are inputs from prediction controller 128. Adder 116 then outputsthe reconstructed block to block memory 118 and loop filter 120. Areconstructed block is also referred to as a local decoded block.

Block Memory

Block memory 118 is storage for storing blocks in a picture to beencoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 118 storesreconstructed blocks output from adder 116.

Loop Filter

Loop filter 120 applies a loop filter to blocks reconstructed by adder116, and outputs the filtered reconstructed blocks to frame memory 122.A loop filter is a filter used in an encoding loop (in-loop filter), andincludes, for example, a deblocking filter (DF), a sample adaptiveoffset (SAO), and an adaptive loop filter (ALF).

In ALF, a least square error filter for removing compression artifactsis applied. For example, one filter from among a plurality of filters isselected for each 2×2 sub-block in the current block based on directionand activity of local gradients, and is applied.

More specifically, first, each sub-block (for example, each 2×2sub-block) is categorized into one out of a plurality of classes (forexample, 15 or 25 classes). The classification of the sub-block is basedon gradient directionality and activity. For example, classificationindex C is derived based on gradient directionality D (for example, 0 to2 or 0 to 4) and gradient activity A (for example, 0 to 4) (for example,C = 5D + A). Then, based on classification index C, each sub-block iscategorized into one out of a plurality of classes (for example, 15 or25 classes).

For example, gradient directionality D is calculated by comparinggradients of a plurality of directions (for example, the horizontal,vertical, and two diagonal directions). Moreover, for example, gradientactivity A is calculated by summing gradients of a plurality ofdirections and quantizing the sum.

The filter to be used for each sub-block is determined from among theplurality of filters based on the result of such categorization.

The filter shape to be used in ALF is, for example, a circular symmetricfilter shape. FIG. 4A through FIG. 4C illustrate examples of filtershapes used in ALF. FIG. 4A illustrates a 5×5 diamond shape filter, FIG.4B illustrates a 7×7 diamond shape filter, and FIG. 4C illustrates a 9×9diamond shape filter. Information indicating the filter shape issignalled at the picture level. Note that the signaling of informationindicating the filter shape need not be performed at the picture level,and may be performed at another level (for example, at the sequencelevel, slice level, tile level, CTU level, or CU level).

The enabling or disabling of ALF is determined at the picture level orCU level. For example, for luma, the decision to apply ALF or not isdone at the CU level, and for chroma, the decision to apply ALF or notis done at the picture level. Information indicating whether ALF isenabled or disabled is signalled at the picture level or CU level. Notethat the signaling of information indicating whether ALF is enabled ordisabled need not be performed at the picture level or CU level, and maybe performed at another level (for example, at the sequence level, slicelevel, tile level, or CTU level).

The coefficients set for the plurality of selectable filters (forexample, 15 or 25 filters) is signalled at the picture level. Note thatthe signaling of the coefficients set need not be performed at thepicture level, and may be performed at another level (for example, atthe sequence level, slice level, tile level, CTU level, CU level, orsub-block level).

Frame Memory

Frame memory 122 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 122 stores reconstructed blocks filtered byloop filter 120.

Intra Predictor

Intra predictor 124 generates a prediction signal (intra predictionsignal) by intra predicting the current block with reference to a blockor blocks in the current picture and stored in block memory 118 (alsoreferred to as intra frame prediction). More specifically, intrapredictor 124 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 128.

For example, intra predictor 124 performs intra prediction by using onemode from among a plurality of predefined intra prediction modes. Theintra prediction modes include one or more non-directional predictionmodes and a plurality of directional prediction modes.

The one or more non-directional prediction modes include, for example,planar prediction mode and DC prediction mode defined in theH.265/high-efficiency video coding (HEVC) standard (see NPL 1).

The plurality of directional prediction modes include, for example, the33 directional prediction modes defined in the H.265/HEVC standard. Notethat the plurality of directional prediction modes may further include32 directional prediction modes in addition to the 33 directionalprediction modes (for a total of 65 directional prediction modes). FIG.5A illustrates 67 intra prediction modes used in intra prediction (twonon-directional prediction modes and 65 directional prediction modes).The solid arrows represent the 33 directions defined in the H.265/HEVCstandard, and the dashed arrows represent the additional 32 directions.

Note that a luma block may be referenced in chroma block intraprediction. In other words, a chroma component of the current block maybe predicted based on a luma component of the current block. Such intraprediction is also referred to as cross-component linear model (CCLM)prediction. Such a chroma block intra prediction mode that references aluma block (referred to as, for example, CCLM mode) may be added as oneof the chroma block intra prediction modes.

Intra predictor 124 may correct post-intra-prediction pixel values basedon horizontal/vertical reference pixel gradients. Intra predictionaccompanied by this sort of correcting is also referred to as positiondependent intra prediction combination (PDPC). Information indicatingwhether to apply PDPC or not (referred to as, for example, a PDPC flag)is, for example, signalled at the CU level. Note that the signaling ofthis information need not be performed at the CU level, and may beperformed at another level (for example, on the sequence level, picturelevel, slice level, tile level, or CTU level).

Inter Predictor

Inter predictor 126 generates a prediction signal (inter predictionsignal) by inter predicting the current block with reference to a blockor blocks in a reference picture, which is different from the currentpicture and is stored in frame memory 122 (also referred to as interframe prediction). Inter prediction is performed per current block orper sub-block (for example, per 4×4 block) in the current block. Forexample, inter predictor 126 performs motion estimation in a referencepicture for the current block or sub-block. Inter predictor 126 thengenerates an inter prediction signal of the current block or sub-blockby motion compensation by using motion information (for example, amotion vector) obtained from motion estimation. Inter predictor 126 thenoutputs the generated inter prediction signal to prediction controller128.

The motion information used in motion compensation is signalled. Amotion vector predictor may be used for the signaling of the motionvector. In other words, the difference between the motion vector and themotion vector predictor may be signalled.

Note that the inter prediction signal may be generated using motioninformation for a neighboring block in addition to motion informationfor the current block obtained from motion estimation. Morespecifically, the inter prediction signal may be generated per sub-blockin the current block by calculating a weighted sum of a predictionsignal based on motion information obtained from motion estimation and aprediction signal based on motion information for a neighboring block.Such inter prediction (motion compensation) is also referred to asoverlapped block motion compensation (OBMC).

In such an OBMC mode, information indicating sub-block size for OBMC(referred to as, for example, OBMC block size) is signalled at thesequence level. Moreover, information indicating whether to apply theOBMC mode or not (referred to as, for example, an OBMC flag) issignalled at the CU level. Note that the signaling of such informationneed not be performed at the sequence level and CU level, and may beperformed at another level (for example, at the picture level, slicelevel, tile level, CTU level, or sub-block level).

Hereinafter, the OBMC mode will be described in further detail. FIG. 5Bis a flowchart and FIG. 5C is a conceptual diagram for illustrating anoutline of a prediction image correction process performed via OBMCprocessing.

First, a prediction image (Pred) is obtained through typical motioncompensation using a motion vector (MV) assigned to the current block.

Next, a prediction image (Pred_L) is obtained by applying a motionvector (MV_L) of the encoded neighboring left block to the currentblock, and a first pass of the correction of the prediction image ismade by superimposing the prediction image and Pred_L.

Similarly, a prediction image (Pred_U) is obtained by applying a motionvector (MV_U) of the encoded neighboring upper block to the currentblock, and a second pass of the correction of the prediction image ismade by superimposing the prediction image resulting from the first passand Pred_U. The result of the second pass is the final prediction image.

Note that the above example is of a two-pass correction method using theneighboring left and upper blocks, but the method may be a three-pass orhigher correction method that also uses the neighboring right and/orlower block.

Note that the region subject to superimposition may be the entire pixelregion of the block, and, alternatively, may be a partial block boundaryregion.

Note that here, the prediction image correction process is described asbeing based on a single reference picture, but the same applies when aprediction image is corrected based on a plurality of referencepictures. In such a case, after corrected prediction images resultingfrom performing correction based on each of the reference pictures areobtained, the obtained corrected prediction images are furthersuperimposed to obtain the final prediction image.

Note that the unit of the current block may be a prediction block and,alternatively, may be a sub-block obtained by further dividing theprediction block.

One example of a method for determining whether to implement OBMCprocessing is by using an obmc_flag, which is a signal that indicateswhether to implement OBMC processing. As one specific example, theencoder determines whether the current block belongs to a regionincluding complicated motion. The encoder sets the obmc_flag to a valueof “1” when the block belongs to a region including complicated motionand implements OBMC processing when encoding, and sets the obmc_flag toa value of “0” when the block does not belong to a region includingcomplication motion and encodes without implementing OBMC processing.The decoder switches between implementing OBMC processing or not bydecoding the obmc_flag written in the stream and performing the decodingin accordance with the flag value.

Note that the motion information may be derived on the decoder sidewithout being signalled. For example, a merge mode defined in theH.265/HEVC standard may be used. Moreover, for example, the motioninformation may be derived by performing motion estimation on thedecoder side. In this case, motion estimation is performed without usingthe pixel values of the current block.

Here, a mode for performing motion estimation on the decoder side willbe described. A mode for performing motion estimation on the decoderside is also referred to as pattern matched motion vector derivation(PMMVD) mode or frame rate up-conversion (FRUC) mode.

One example of FRUC processing is illustrated in FIG. 5D. First, acandidate list (a candidate list may be a merge list) of candidates eachincluding a motion vector predictor is generated with reference tomotion vectors of encoded blocks that spatially or temporally neighborthe current block. Next, the best candidate MV is selected from among aplurality of candidate MVs registered in the candidate list. Forexample, evaluation values for the candidates included in the candidatelist are calculated and one candidate is selected based on thecalculated evaluation values.

Next, a motion vector for the current block is derived from the motionvector of the selected candidate. More specifically, for example, themotion vector for the current block is calculated as the motion vectorof the selected candidate (best candidate MV), as-is. Alternatively, themotion vector for the current block may be derived by pattern matchingperformed in the vicinity of a position in a reference picturecorresponding to the motion vector of the selected candidate. In otherwords, when the vicinity of the best candidate MV is searched via thesame method and an MV having a better evaluation value is found, thebest candidate MV may be updated to the MV having the better evaluationvalue, and the MV having the better evaluation value may be used as thefinal MV for the current block. Note that a configuration in which thisprocessing is not implemented is also acceptable.

The same processes may be performed in cases in which the processing isperformed in units of sub-blocks.

Note that an evaluation value is calculated by calculating thedifference in the reconstructed image by pattern matching performedbetween a region in a reference picture corresponding to a motion vectorand a predetermined region. Note that the evaluation value may becalculated by using some other information in addition to thedifference.

The pattern matching used is either first pattern matching or secondpattern matching. First pattern matching and second pattern matching arealso referred to as bilateral matching and template matching,respectively.

In the first pattern matching, pattern matching is performed between twoblocks along the motion trajectory of the current block in two differentreference pictures. Therefore, in the first pattern matching, a regionin another reference picture conforming to the motion trajectory of thecurrent block is used as the predetermined region for theabove-described calculation of the candidate evaluation value.

FIG. 6 is for illustrating one example of pattern matching (bilateralmatching) between two blocks along a motion trajectory. As illustratedin FIG. 6 , in the first pattern matching, two motion vectors (MV0, MV1)are derived by finding the best match between two blocks along themotion trajectory of the current block (Cur block) in two differentreference pictures (Ref0, Ref1). More specifically, a difference between(i) a reconstructed image in a specified position in a first encodedreference picture (Ref0) specified by a candidate MV and (ii) areconstructed picture in a specified position in a second encodedreference picture (Ref1) specified by a symmetrical MV scaled at adisplay time interval of the candidate MV may be derived, and theevaluation value for the current block may be calculated by using thederived difference. The candidate MV having the best evaluation valueamong the plurality of candidate MVs may be selected as the final MV

Under the assumption of continuous motion trajectory, the motion vectors(MV0, MV1) pointing to the two reference blocks shall be proportional tothe temporal distances (TD0, TD1) between the current picture (Cur Pic)and the two reference pictures (Ref0, Ref1). For example, when thecurrent picture is temporally between the two reference pictures and thetemporal distance from the current picture to the two reference picturesis the same, the first pattern matching derives a mirror basedbi-directional motion vector.

In the second pattern matching, pattern matching is performed between atemplate in the current picture (blocks neighboring the current block inthe current picture (for example, the top and/or left neighboringblocks)) and a block in a reference picture. Therefore, in the secondpattern matching, a block neighboring the current block in the currentpicture is used as the predetermined region for the above-describedcalculation of the candidate evaluation value.

FIG. 7 is for illustrating one example of pattern matching (templatematching) between a template in the current picture and a block in areference picture. As illustrated in FIG. 7 , in the second patternmatching, a motion vector of the current block is derived by searching areference picture (Ref0) to find the block that best matches neighboringblocks of the current block (Cur block) in the current picture (CurPic). More specifically, a difference between (i) a reconstructed imageof an encoded region that is both or one of the neighboring left andneighboring upper region and (ii) a reconstructed picture in the sameposition in an encoded reference picture (Ref0) specified by a candidateMV may be derived, and the evaluation value for the current block may becalculated by using the derived difference. The candidate MV having thebest evaluation value among the plurality of candidate MVs may beselected as the best candidate MV.

Information indicating whether to apply the FRUC mode or not (referredto as, for example, a FRUC flag) is signalled at the CU level. Moreover,when the FRUC mode is applied (for example, when the FRUC flag is set totrue), information indicating the pattern matching method (first patternmatching or second pattern matching) is signalled at the CU level. Notethat the signaling of such information need not be performed at the CUlevel, and may be performed at another level (for example, at thesequence level, picture level, slice level, tile level, CTU level, orsub-block level).

Here, a mode for deriving a motion vector based on a model assuminguniform linear motion will be described. This mode is also referred toas a bi-directional optical flow (BIO) mode.

FIG. 8 is for illustrating a model assuming uniform linear motion. InFIG. 8 , (v_(x), v_(y)) denotes a velocity vector, and τ₀ and τ₁ denotetemporal distances between the current picture (Cur Pic) and tworeference pictures (Ref₀, Ref ₁). (MVx₀, MVy₀) denotes a motion vectorcorresponding to reference picture Ref₀, and (MVx₁, MVy₁) denotes amotion vector corresponding to reference picture Ref₁.

Here, under the assumption of uniform linear motion exhibited byvelocity vector (v_(x), v_(y)), (MVx₀, MVy₀) and (MVx₁, MVy₁) arerepresented as (v_(x)τ₀, v_(y)τ₀) and (-v_(x)τ₁, -v_(y)τ₁),respectively, and the following optical flow equation is given. MATH. 1

$\begin{matrix}{{\partial I^{(k)}}/{{\partial t + v_{x}\partial I^{(k)}}/{{\partial x + v_{y}\partial I^{(k)}}/{\partial y = 0.}}}} & \text{­­­(1)}\end{matrix}$

Here, I^((k)) denotes a luma value from reference picture k (k = 0, 1)after motion compensation. This optical flow equation shows that the sumof (i) the time derivative of the luma value, (ii) the product of thehorizontal velocity and the horizontal component of the spatial gradientof a reference picture, and (iii) the product of the vertical velocityand the vertical component of the spatial gradient of a referencepicture is equal to zero. A motion vector of each block obtained from,for example, a merge list is corrected pixel by pixel based on acombination of the optical flow equation and Hermite interpolation.

Note that a motion vector may be derived on the decoder side using amethod other than deriving a motion vector based on a model assuminguniform linear motion. For example, a motion vector may be derived foreach sub-block based on motion vectors of neighboring blocks.

Here, a mode in which a motion vector is derived for each sub-blockbased on motion vectors of neighboring blocks will be described. Thismode is also referred to as affine motion compensation prediction mode.

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks. In FIG. 9A, the currentblock includes 16 4×4 sub-blocks. Here, motion vector v₀ of the top leftcorner control point in the current block is derived based on motionvectors of neighboring sub-blocks, and motion vector v₁ of the top rightcorner control point in the current block is derived based on motionvectors of neighboring blocks. Then, using the two motion vectors v₀ andv₁, the motion vector (v_(x), v_(y)) of each sub-block in the currentblock is derived using Equation 2 below. MATH. 2

$\begin{matrix}\left\{ \begin{matrix}{v_{x} = \frac{\left( {v_{1x} - v_{0x}} \right)}{w}x - \frac{\left( {v_{1y} - v_{0y}} \right)}{w}y + v_{0x}} \\{v_{y} = \frac{\left( {v_{1y} - v_{0y}} \right)}{w}x - \frac{\left( {v_{1x} - v_{0x}} \right)}{w}y + v_{0y}}\end{matrix} \right) & \text{­­­(2)}\end{matrix}$

Here, x and y are the horizontal and vertical positions of thesub-block, respectively, and w is a predetermined weighted coefficient.

Such an affine motion compensation prediction mode may include a numberof modes of different methods of deriving the motion vectors of the topleft and top right corner control points. Information indicating such anaffine motion compensation prediction mode (referred to as, for example,an affine flag) is signalled at the CU level. Note that the signaling ofinformation indicating the affine motion compensation prediction modeneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, CTU level, or sub-block level).

Prediction Controller

Prediction controller 128 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto subtractor 104 and adder 116.

Here, an example of deriving a motion vector via merge mode in a currentpicture will be given. FIG. 9B is for illustrating an outline of aprocess for deriving a motion vector via merge mode.

First, an MV predictor list in which candidate MV predictors areregistered is generated. Examples of candidate MV predictors include:spatially neighboring MV predictors, which are MVs of encoded blockspositioned in the spatial vicinity of the current block; a temporallyneighboring MV predictor, which is an MV of a block in an encodedreference picture that neighbors a block in the same location as thecurrent block; a combined MV predictor, which is an MV generated bycombining the MV values of the spatially neighboring MV predictor andthe temporally neighboring MV predictor; and a zero MV predictor, whichis an MV whose value is zero.

Next, the MV of the current block is determined by selecting one MVpredictor from among the plurality of MV predictors registered in the MVpredictor list.

Furthermore, in the variable-length encoder, a merge_idx, which is asignal indicating which MV predictor is selected, is written and encodedinto the stream.

Note that the MV predictors registered in the MV predictor listillustrated in FIG. 9B constitute one example. The number of MVpredictors registered in the MV predictor list may be different from thenumber illustrated in FIG. 9B, the MV predictors registered in the MVpredictor list may omit one or more of the types of MV predictors givenin the example in FIG. 9B, and the MV predictors registered in the MVpredictor list may include one or more types of MV predictors inaddition to and different from the types given in the example in FIG.9B.

Note that the final MV may be determined by performing DMVR processing(to be described later) by using the MV of the current block derived viamerge mode.

Here, an example of determining an MV by using DMVR processing will begiven.

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing.

First, the most appropriate MVP set for the current block is consideredto be the candidate MV, reference pixels are obtained from a firstreference picture, which is a picture processed in the L0 direction inaccordance with the candidate MV, and a second reference picture, whichis a picture processed in the L1 direction in accordance with thecandidate MV, and a template is generated by calculating the average ofthe reference pixels.

Next, using the template, the surrounding regions of the candidate MVsof the first and second reference pictures are searched, and the MV withthe lowest cost is determined to be the final MV. Note that the costvalue is calculated using, for example, the difference between eachpixel value in the template and each pixel value in the regionssearched, as well as the MV value.

Note that the outlines of the processes described here are fundamentallythe same in both the encoder and the decoder.

Note that processing other than the processing exactly as describedabove may be used, so long as the processing is capable of deriving thefinal MV by searching the surroundings of the candidate MV

Here, an example of a mode that generates a prediction image by usingLIC processing will be given.

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing.

First, an MV is extracted for obtaining, from an encoded referencepicture, a reference image corresponding to the current block.

Next, information indicating how the luminance value changed between thereference picture and the current picture is extracted and a luminancecorrection parameter is calculated by using the luminance pixel valuesfor the encoded left neighboring reference region and the encoded upperneighboring reference region, and the luminance pixel value in the samelocation in the reference picture specified by the MV.

The prediction image for the current block is generated by performing aluminance correction process by using the luminance correction parameteron the reference image in the reference picture specified by the MV.

Note that the shape of the surrounding reference region illustrated inFIG. 9D is just one example; the surrounding reference region may have adifferent shape.

Moreover, although a prediction image is generated from a singlereference picture in this example, in cases in which a prediction imageis generated from a plurality of reference pictures as well, theprediction image is generated after performing a luminance correctionprocess, via the same method, on the reference images obtained from thereference pictures.

One example of a method for determining whether to implement LICprocessing is by using an lic_flag, which is a signal that indicateswhether to implement LIC processing. As one specific example, theencoder determines whether the current block belongs to a region ofluminance change. The encoder sets the lic_flag to a value of “1” whenthe block belongs to a region of luminance change and implements LICprocessing when encoding, and sets the lic_flag to a value of “0” whenthe block does not belong to a region of luminance change and encodeswithout implementing LIC processing. The decoder switches betweenimplementing LIC processing or not by decoding the lic_flag written inthe stream and performing the decoding in accordance with the flagvalue.

One example of a different method of determining whether to implementLIC processing is determining so in accordance with whether LICprocessing was determined to be implemented for a surrounding block. Inone specific example, when merge mode is used on the current block,whether LIC processing was applied in the encoding of the surroundingencoded block selected upon deriving the MV in the merge mode processingmay be determined, and whether to implement LIC processing or not can beswitched based on the result of the determination. Note that in thisexample, the same applies to the processing performed on the decoderside.

Decoder Outline

Next, a decoder capable of decoding an encoded signal (encodedbitstream) output from encoder 100 will be described. FIG. 10 is a blockdiagram illustrating a functional configuration of decoder 200 accordingto Embodiment 1. Decoder 200 is a moving picture/picture decoder thatdecodes a moving picture/picture block by block.

As illustrated in FIG. 10 , decoder 200 includes entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, block memory210, loop filter 212, frame memory 214, intra predictor 216, interpredictor 218, and prediction controller 220.

Decoder 200 is realized as, for example, a generic processor and memory.In this case, when a software program stored in the memory is executedby the processor, the processor functions as entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, loop filter212, intra predictor 216, inter predictor 218, and prediction controller220. Alternatively, decoder 200 may be realized as one or more dedicatedelectronic circuits corresponding to entropy decoder 202, inversequantizer 204, inverse transformer 206, adder 208, loop filter 212,intra predictor 216, inter predictor 218, and prediction controller 220.

Hereinafter, each component included in decoder 200 will be described.

Entropy Decoder

Entropy decoder 202 entropy decodes an encoded bitstream. Morespecifically, for example, entropy decoder 202 arithmetic decodes anencoded bitstream into a binary signal. Entropy decoder 202 thendebinarizes the binary signal. With this, entropy decoder 202 outputsquantized coefficients of each block to inverse quantizer 204.

Inverse Quantizer

Inverse quantizer 204 inverse quantizes quantized coefficients of ablock to be decoded (hereinafter referred to as a current block), whichare inputs from entropy decoder 202. More specifically, inversequantizer 204 inverse quantizes quantized coefficients of the currentblock based on quantization parameters corresponding to the quantizedcoefficients. Inverse quantizer 204 then outputs the inverse quantizedcoefficients (i.e., transform coefficients) of the current block toinverse transformer 206.

Inverse Transformer

Inverse transformer 206 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 204.

For example, when information parsed from an encoded bitstream indicatesapplication of EMT or AMT (for example, when the AMT flag is set totrue), inverse transformer 206 inverse transforms the transformcoefficients of the current block based on information indicating theparsed transform type.

Moreover, for example, when information parsed from an encoded bitstreamindicates application of NSST, inverse transformer 206 applies asecondary inverse transform to the transform coefficients.

Adder

Adder 208 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 206, and prediction samples,which is an input from prediction controller 220. Adder 208 then outputsthe reconstructed block to block memory 210 and loop filter 212.

Block Memory

Block memory 210 is storage for storing blocks in a picture to bedecoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 210 storesreconstructed blocks output from adder 208.

Loop Filter

Loop filter 212 applies a loop filter to blocks reconstructed by adder208, and outputs the filtered reconstructed blocks to frame memory 214and, for example, a display device.

When information indicating the enabling or disabling of ALF parsed froman encoded bitstream indicates enabled, one filter from among aplurality of filters is selected based on direction and activity oflocal gradients, and the selected filter is applied to the reconstructedblock.

Frame Memory

Frame memory 214 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 214 stores reconstructed blocks filtered byloop filter 212.

Intra Predictor

Intra predictor 216 generates a prediction signal (intra predictionsignal) by intra prediction with reference to a block or blocks in thecurrent picture and stored in block memory 210. More specifically, intrapredictor 216 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 220.

Note that when an intra prediction mode in which a chroma block is intrapredicted from a luma block is selected, intra predictor 216 may predictthe chroma component of the current block based on the luma component ofthe current block.

Moreover, when information indicating the application of PDPC is parsedfrom an encoded bitstream, intra predictor 216 correctspost-intra-prediction pixel values based on horizontal/verticalreference pixel gradients.

[Inter Predictor]

Inter predictor 218 predicts the current block with reference to areference picture stored in frame memory 214. Inter prediction isperformed per current block or per sub-block (for example, per 4×4block) in the current block. For example, inter predictor 218 generatesan inter prediction signal of the current block or sub-block by motioncompensation by using motion information (for example, a motion vector)parsed from an encoded bitstream, and outputs the inter predictionsignal to prediction controller 220.

Note that when the information parsed from the encoded bitstreamindicates application of OBMC mode, inter predictor 218 generates theinter prediction signal using motion information for a neighboring blockin addition to motion information for the current block obtained frommotion estimation.

Moreover, when the information parsed from the encoded bitstreamindicates application of FRUC mode, inter predictor 218 derives motioninformation by performing motion estimation in accordance with thepattern matching method (bilateral matching or template matching) parsedfrom the encoded bitstream. Inter predictor 218 then performs motioncompensation using the derived motion information.

Moreover, when BIO mode is to be applied, inter predictor 218 derives amotion vector based on a model assuming uniform linear motion. Moreover,when the information parsed from the encoded bitstream indicates thataffine motion compensation prediction mode is to be applied, interpredictor 218 derives a motion vector of each sub-block based on motionvectors of neighboring blocks.

Prediction Controller

Prediction controller 220 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto adder 208.

First Aspect

A first aspect describes an example of inter prediction processingperformed by inter predictor 126. Inter predictor 126 obtains at leasttwo items of prediction information for a first partition included in avideo. For example, the prediction information may be a motion vector.Inter predictor 126 derives at least one template from a plurality ofneighboring samples which neighbor the first partition. For example, aneighboring sample may be a plurality of pixels which neighbor the firstpartition. Note that a partition is a region included in a video. Morespecifically, a partition may be a block which is a region in a pictureincluded in a video. Further, a template may be a reference block, forexample.

Inter predictor 126 calculates at least two template costs, using atleast one template and at least two items of prediction information. Inthis aspect, a template cost (hereafter, simply referred to as a cost)is used to determine a splitting direction for the first partition. Inother words, inter predictor 126 determines the splitting direction forthe first partition using at least two costs. Accordingly, a secondpartition and a third partition are split from the first partitionaccording to the splitting direction. Stated differently, the second andthird partitions are obtained by splitting the first partition. Thefollowing specifically describes inter prediction processing accordingto this aspect with reference to the drawings.

FIG. 11 is a flowchart illustrating an example of inter predictionprocessing in the first aspect. Here, an example of processing ofperforming inter prediction on the second partition and the thirdpartition is to be described.

As illustrated in FIG. 11 , in step S1001, a first motion vector isobtained for the second partition. Similarly, a second motion vector isobtained for the third partition. For example, the first motion vectorand the second motion vector may be derived from blocks spatially ortemporally near the first partition. Here, the first motion vector andthe second motion vector are derived from blocks spatially neighboringthe first partition.

FIG. 12 illustrates examples of the second partition and the thirdpartition in the first aspect. Here, examples of the second partitionand the third partition which are split from the first partition areillustrated. The second partition and the third partition may betriangular partitions as illustrated in (a) and (b) of FIG. 12 , and maybe rectangular partitions as illustrated in (c) and (d) of FIG. 12 . Theshape of the second partition and the third partition is not limited tothe above shape, and the second partition and the third partition may benon-rectangular partitions. Examples of a non-rectangular shape includea trapezoid, a pentagon, a hexagon, and so on.

Next, in step S1002, at least two costs for a first template and asecond template are calculated using the first motion vector and thesecond motion vector obtained in step S1001. The first template and thesecond template are derived from a plurality of neighboring sampleswhich neighbor the first partition. At least one of the first templateand the second template may be derived from an upper neighboring samplelocated above the first partition among the plurality of neighboringsamples. Further, at least one of the first template and the secondtemplate may be derived from a left neighboring sample located on theleft of the first partition among the plurality of neighboring samples.Here, the first template is derived from the upper neighboring sampleabove the first partition. Further, the second template is derived fromthe left neighboring sample on the left of the first partition.Specifically, as illustrated in (a) of FIG. 13 , the first template is aneighboring block having a side that is the upper side of the firstpartition, and the second template is a neighboring block having a sidethat is the left side of the first partition.

FIG. 13 illustrates an example of calculation of costs in the firstaspect. In FIG. 13 , (a) illustrates examples of templates. In FIG. 13 ,(b) illustrates examples of at least two costs calculated using at leastone template and at least two items of prediction information. In FIG.13 , (c) is a diagram for describing examples of the calculated costs.

As illustrated in (b) of FIG. 13 , at least two costs are calculated foreach of the first template and the second template, using the firstmotion vector and the second motion vector, in step S1002. A first costis calculated using the first template and the first motion vector, anda second cost is calculated using the first template and the secondmotion vector. Further, a third cost is calculated using the secondtemplate and the first motion vector, and a fourth cost is calculatedusing the second template and the second motion vector. Calculation ofcosts may include at least a minus operation. For example, costcalculation which includes a minus operation may be the sum of absolutedifference (SAD), sum of square error (SSE), hadamard difference (HAD)or mean-removed SAD.

Costs are obtained by calculation which includes a minus operation forcalculating a difference between reconstructed samples in one templateand samples inter-predicted using a predetermined motion vector for theone template. Here, as illustrated in (c) of FIG. 13 , the first cost isa cost between reconstructed samples in the first template and samplesinter-predicted using the first motion vector for the first template.The second cost is a cost between reconstructed samples in the firsttemplate and samples inter-predicted using the second motion vector forthe first template. The third cost is a cost between reconstructedsamples in the second template and samples inter-predicted using thefirst motion vector for the second template. The fourth cost is a costbetween reconstructed samples in the second template and inter-predictedsamples using the second motion vector for the second template.

Next, in step S1003, the splitting direction for the first partition isdetermined using the at least two costs obtained in step S1002. Asdescribed with reference to FIG. 12 , the second partition and the thirdpartition split from the first partition may be triangular partitions.In this case, the first partition is split in a diagonal direction suchas a direction from the top-left corner to the bottom-right corner or adirection from the top-right corner to the bottom-left corner. Asdescribed with reference to FIG. 12 , the second partition and the thirdpartition may be rectangular partitions. In this case, the firstpartition is split in the horizontal or vertical direction. Suchsplitting directions are to be more specifically described, withreference to FIGS. 14 and 15 .

FIG. 14 illustrates examples of processing in step S1003 in FIG. 11 .FIG. 14 illustrates examples of determining the splitting direction whenthe first partition is split into two triangular partitions. Asillustrated in (a) of FIG. 14 , if the sum of the first cost and thethird cost is less than or equal to the sum of the second cost and thefourth cost, the splitting direction for the first partition is adirection from the top-right corner to the bottom-left corner. Asillustrated in (b) of FIG. 14 , if the sum of the first cost and thethird cost is greater than the sum of the second cost and the fourthcost, the splitting direction for the first partition is a directionfrom the top-left corner to the bottom-right corner.

FIG. 15 illustrates other examples of processing in step S1003 in FIG.11 . FIG. 15 illustrates examples of determining the splitting directionwhen the first partition is split into two rectangular partitions. Asillustrated in (a) of FIG. 15 , if the first cost is less than or equalto the third cost, the splitting direction for the first partition ishorizontal. As illustrated in (b) of FIG. 15 , if the first cost isgreater than the third cost, the splitting direction for the firstpartition is vertical.

Next, in step S1004, the first partition is encoded or decoded, usingthe splitting direction determined in step S1003 and the first motionvector and the second motion vector obtained in step S1001. Encoding thefirst partition may include writing a parameter into a bitstream.Similarly, decoding the first partition may include reading a parameterfrom a bitstream.

FIG. 16 illustrates examples of parameters in the first aspect.

As illustrated in FIG. 16 , the first motion vector and the secondmotion vector are predicted from a first motion vector candidate listand a second motion vector candidate list, respectively. Parameters(parameter values in FIG. 16 ) are associated with the first motionvector of the second partition and the second motion vector of the thirdpartition. As illustrated with reference to FIGS. 14 and 15 , thesplitting direction for the first partition is determined using costs.Accordingly, each parameter may be associated with motion vectors of thesecond partition and the third partition split from the first partition,but may not be associated with the splitting direction for the firstpartition. For example, as illustrated in FIG. 16 , if parameter valuesin the first and second rows are compared, the splitting directions forthe first partition are different for the parameter values, yet themotion vectors of the first partition and the second partition are thesame. Accordingly, it is not necessary to assign, to the parameter valuein the second row, a parameter value different from the parameter valuein the first row. Accordingly, the encoding amount can be reduced.

The above is a description of an example in which motion vectors areused as at least two items of prediction information when the secondpartition and the third partition are inter-predicted, but the presentdisclosure is not limited to this. For example, the at least two itemsof prediction information may be merge candidates.

For example, when the second partition and the third partition areintra-predicted, the at least two items of prediction information may bemerge candidates or may be intra prediction modes. FIG. 17 is aflowchart illustrating an example of intra prediction processing in thefirst aspect.

As illustrated in FIG. 17 , in step S2001, a first intra prediction modeis obtained for the second partition, and a second intra prediction modeis obtained for the third partition. The first intra prediction mode andthe second intra prediction mode may be derived from blocks temporallynear the first partition.

Next, in step S2002, at least two costs for the first template and thesecond template are calculated using the first intra prediction mode andthe second intra prediction mode obtained in step S2001. Note thatcalculation of costs is as described in the above example of interprediction processing.

Next, in step S2003, the splitting direction for the first partition isdetermined using the at least two costs calculated in step S2002.

Next, in step S2004, the first partition is encoded or decoded using thesplitting direction determined in step S2003, and the first intraprediction mode and the second intra prediction mode obtained in stepS2001. At this time, a parameter may be associated with the first intraprediction mode and the second intra prediction mode, but does not needto be associated with the splitting direction for the first partition.

Note that the term “motion vector” used in the description regarding theinter-predicted second partition and the inter-predicted third partitionmay be replaced with the term “intra prediction mode”.

Technical Advantages of First Aspect

According to this aspect, template costs for determining the splittingdirection for splitting one partition into two partitions areintroduced. This eliminates the necessity of encoding or decoding thesplitting direction, and thus improves encoding efficiency.

Combination With Other Aspects

At least a portion of the first aspect may be combined with at least aportion of one or more other aspects of the present disclosure describedbelow. A portion of the processing in the flowcharts, a portion of theconfiguration of a device, syntax, and/or other features may be combinedwith other aspects. Not all the processing/elements are necessarilyneeded. The device/method may include a portion of the processing/one ormore of the elements. The above processing may be performed by a decodersimilarly to an encoder.

Second Aspect

In this aspect, template costs (hereafter, simply referred to as costs)are used to determine motion vectors of a second partition and a thirdpartition. In the first aspect, costs are used to determine thesplitting direction for the first partition, yet the splitting directionfor the first partition may be determined in advance in this aspect. Thesecond partition and the third partition are split from the firstpartition according to the splitting direction.

FIG. 18 is a flowchart illustrating an example of inter predictionprocessing in the second aspect.

As illustrated in FIG. 18 , in step S3001, the first partition is splitinto the second partition and the third partition according to thesplitting direction. As illustrated in (a) and (b) of FIG. 12 , thesplitting direction may be a diagonal direction such as a direction fromthe top-left corner to the bottom-right corner of the first partition ora direction from the top-right corner to the bottom-left corner of thefirst partition. Furthermore, for example, the splitting direction maybe vertical and horizontal, as illustrated in (c) and (d) of FIG. 12 .

Next, in step S3002, at least two motion vectors including a firstmotion vector and a second motion vector of the first partition areobtained.

Next, in step S3003, at least two costs for the first template and thesecond template are calculated using the at least two motion vectorsobtained in step S3002. More specifically, as illustrated in FIG. 13 ,two costs are calculated for each of the first template and the secondtemplate, using the first motion vector and the second motion vector. Inthis example, for the first template, the first cost is calculated usingthe first motion vector, and the second cost is calculated using thesecond motion vector. Similarly, also for the second template, the thirdcost and the fourth cost are calculated using the first motion vectorand the second motion vector, respectively. Since calculation of costsis the same as the calculation described in the first aspect, adescription thereof is omitted here.

Next, in step S3004, using the at least two costs, one of the at leasttwo motion vectors is assigned to the second partition, and another ofthe at least two motion vectors is assigned to the third partition. Forexample, as illustrated in FIGS. 19 and 20 , when the at least twomotion vectors are the first motion vector and the second motion vector,at least two costs for each of the first template and the secondtemplate are calculated using the first motion vector and the secondmotion vector. Then, using the at least two costs, one of the firstmotion vector and the second motion vector is selected for the secondpartition, and the other of the first motion vector and the secondmotion vector is assigned to the third partition.

The following more specifically describes processing in step S3004, withreference to FIGS. 19 and 20 . FIG. 19 illustrates an example ofprocessing in step S3004 in FIG. 18 . FIG. 20 illustrates anotherexample of the processing in step S3004 in FIG. 18 . Specifically, FIG.19 illustrates examples of selecting motion vectors for the secondpartition and the third partition when the second partition and thethird partition are triangular partitions. FIG. 20 illustrates examplesof selecting motion vectors for the second partition and the thirdpartition when the second partition and the third partition arerectangular partitions.

First, examples illustrated in FIG. 19 are to be described. In theexamples illustrated in (a) and (b) of FIG. 19 , the first partition issplit in the direction from the top-right corner to the bottom-leftcorner. At this time, the second partition is a triangular partition inthe upper-left half of the first partition, and the third partition is atriangular partition in the lower right half of the first partition. Asillustrated in (a) of FIG. 19 , if the sum of the first cost and thethird cost is less than or equal to the sum of the second cost and thefourth cost, the first motion vector is selected for the secondpartition, and the second motion vector is assigned to the thirdpartition. As illustrated in (b) of FIG. 19 , if the sum of the firstcost and the third cost is greater than the sum of the second cost andthe fourth cost, the second motion vector is selected for the secondpartition, and the first motion vector is assigned to the firstpartition.

In the examples illustrated in (c) and (d) of FIG. 19 , the firstpartition is split into the direction from the top-left corner to thebottom-right corner. At this time, the second partition is a triangularpartition in the upper-right half of the first partition, and the thirdpartition is a triangular partition in the lower-left half of the firstpartition. As illustrated in (c) of FIG. 19 , if the sum of the firstcost and the fourth cost is less than or equal to the sum of the secondcost and the third cost, the first motion vector is selected for thesecond partition, and the second motion vector is assigned to the thirdpartition. As illustrated in (d) of FIG. 19 , if the sum of the firstcost and the fourth cost is greater than the sum of the second cost andthe third cost, the second motion vector is selected for the secondpartition, and the first motion vector is assigned to the thirdpartition.

Next, examples illustrated in FIG. 20 are to be described. In theexamples illustrated in (a) and (b) of FIG. 20 , the first partition issplit horizontally. At this time, the second partition is a rectangularpartition in the upper half of the first partition, and the thirdpartition is a rectangular partition in the lower half of the firstpartition. As illustrated in (a) of FIG. 20 , if the first cost is lessthan or equal to the second cost, the first motion vector is selectedfor the second partition, and the second motion vector is assigned tothe third partition. As illustrated in (b) of FIG. 20 , if the firstcost is greater than the second cost, the second motion vector isselected for the second partition, and the first motion vector isassigned to the third partition.

In the examples illustrated in (c) and (d) of FIG. 20 , the firstpartition is split vertically. At this time, the second partition is arectangular partition in the left half of the first partition, and thethird partition is a rectangular partition in the right half of thefirst partition. As illustrated in (c) of FIG. 20 , if the third cost isless than or equal to the fourth cost, the first motion vector isselected for the second partition, and the second motion vector isassigned to the third partition. As illustrated in (d) of FIG. 20 , ifthe third cost is greater than the fourth cost, the second motion vectoris selected for the second partition, and the first motion vector isassigned to the third partition.

Next, in step S3005, the first partition is encoded or decoded accordingto the splitting direction and the first motion vector and the secondmotion vector obtained in step S3002. Encoding the first partition mayinclude writing a parameter into a bitstream. Similarly, decoding thefirst partition may include reading a parameter from a bitstream.

FIG. 21 illustrates examples of parameters in the second aspect. Asillustrated in FIG. 21 , the first motion vector and the second motionvector are both predicted from a motion vector candidate list. Thus, aparameter does not need to indicate which of the first motion vector andthe second motion vector indicates motion of the second partition andwhich of the second motion vector and the second motion vector indicatesmotion of the third partition. Accordingly, the splitting direction forthe first partition and at least two motion vectors may be associatedwith each parameter in the second aspect (each parameter value in FIG.21 ). This eliminates the necessity of encoding and decoding assignmentinformation for each of at least two motion vectors, and thus theencoding amount can be reduced. For example, as shown by the parametersin the second row and the third row of the table illustrated in FIG. 21, if the splitting direction for the first partition is the same and ifthe combinations of two motion vectors are the same, the conditions forthe parameters are determined to be the same, and the parameter in thethird row is eliminated.

The above has given a description of an example in which motion vectorsare used as at least two items of prediction information when the secondpartition and the third partition are inter-predicted. For example, theat least two items of prediction information may be merge candidates.

For example, when the second partition and the third partition areintra-predicted, at least two items of prediction information may bemerge candidates or may be intra prediction modes. FIG. 22 is aflowchart illustrating an example of the intra prediction processing inthe second aspect.

As illustrated in FIG. 22 , in step S4001, the first partition is splitinto the second partition and the third partition according to thesplitting direction. Next, in step S4002, at least two intra predictionmodes including a first intra prediction mode and a second intraprediction mode for the first partition are obtained. Next, in stepS4003, at least two costs for the first template and the second templateare calculated using the at least two intra prediction modes obtained instep S4002. Note that calculation of costs is as described in theexample of inter prediction processing described above.

Next, in step S4004, using the at least two costs calculated in stepS4003, one of the at least two intra prediction modes is assigned to thesecond partition, and another of the at least two intra prediction modesis assigned to the third partition.

Next, in step S4005, the first partition is encoded or decoded using thesplitting direction and the intra prediction modes obtained in stepS4002. At this time, a parameter may be associated with the splittingdirection and the at least two intra prediction modes for the firstpartition.

Accordingly, the term “motion vector” used in the description of theinter-predicted second and third partitions may be replaced with theterm “intra prediction mode” when the second and third partitions areintra-predicted.

Technical Advantages of Second Aspect

This aspect introduces motion vectors of the second partition and thethird partition which are split from the first partition, and templatecosts for determining intra prediction modes. According to this aspect,the motion vectors or intra prediction modes for the second partitionand the third partition are encoded together without indicating whichmotion vector or which intra prediction mode is for the second partitionand which motion vector is for the third partition. This eliminates thenecessity of encoding or decoding information which indicatesassociation between the first and second motion vectors and the firstand third partitions, and thus encoding efficiency can be improvedaccording to this aspect.

Combination With Other Aspects

At least a portion of the second aspect may be combined with at least aportion of one or more other aspects of the present disclosure. Aportion of the processing in the flowcharts, a portion of theconfiguration of a device, syntax, and/or other features may be combinedwith other aspects. Not all the processing/elements are necessarilyneeded. The device/method may include a portion of processing/one ormore of the elements. The above processing may be performed by adecoder, similarly to an encoder.

For example, the first aspect and the second aspect may be combined.Specifically, the costs in the first aspect and the costs in the secondaspect may be combined. As described above, the costs in the firstaspect are used to determine the splitting direction for the firstpartition. Further, the costs in the second aspect are used to determinethe motion vectors of the second partition and the third partition whichare split from the first partition according to the splitting direction.Accordingly, costs in an aspect obtained by combining the first aspectand the second aspect (hereafter referred to as a combined aspect) areused to determine a splitting direction for the first partition andmotion vectors of the second and third partitions split from the firstpartition according to the splitting direction, for example. Thefollowing more specifically describes an example of a combined aspect,with reference to the drawings. Note that also in this example, thesecond partition and the third partition are inter-predicted.

FIG. 23 is a flowchart illustrating an example of inter predictionprocessing in the combined aspect. As illustrated in FIG. 23 , in stepS5001, at least two motion vectors including the first motion vector andthe second motion vector of the first partition are obtained.

Next, in step S5002, at least two costs are calculated for the firsttemplate and the second template using the at least two motion vectors.More specifically, similarly to the example illustrated in FIG. 13 , twocosts are calculated for each of the first template and the secondtemplate, using the first motion vector and the second motion vectorobtained in step S5001. Specific costs and calculation thereof aredescribed in the first aspect, and thus a description here is omitted.

Next, in step S5003, the splitting direction for the first partition isdetermined using the at least two costs calculated in step S5002. Thesplitting direction for the first partition may be a diagonal directionsuch as a direction from the top-left corner to the bottom-right cornerof the first partition or a direction from the top-right corner to thebottom-left corner of the first partition, or may be horizontal orvertical. As described above, when the splitting direction for the firstpartition is a diagonal direction, the second partition and the thirdpartition are triangular, whereas when the splitting direction for thefirst partition is horizontal or vertical, the second partition and thethird partition are rectangular.

Next, in step S5004, using the at least two costs obtained in stepS5002, one of the at least two motion vectors is assigned to the secondpartition, and another of the at least two motion vectors is assigned tothe third partition.

The following more specifically describes processing in steps S5003 andS5004, with reference to FIGS. 24 and 25 . FIG. 24 illustrates anexample of processing in steps S5003 and S5004 in FIG. 23 . FIG. 25illustrates other examples of processing in steps S5003 and S5004 inFIG. 23 . Specifically, FIG. 24 illustrates examples in which when thesecond partition and the third partition are triangular, the splittingdirection for the first partition is determined, and motion vectors ofthe second partition and the third partition are selected. Further, FIG.25 illustrates examples in which when the second partition and the thirdpartition are rectangular, the splitting direction for the firstpartition is determined, and motion vectors of the second partition andthe third partition are selected.

First, the examples illustrated in FIG. 24 are to be described. Thefirst partitions are split into two triangular partitions in FIG. 24 .

In the example illustrated in (a) of FIG. 24 , when the first cost isless than or equal to the second cost and the third cost is less than orequal to the fourth cost, the splitting direction for the firstpartition is determined to be a direction from the top-right corner tothe bottom-left corner. At this time, the first motion vector isselected for the second partition, and the second motion vector isassigned to the third partition.

In the example illustrated in (b) of FIG. 24 , when the first cost isgreater than the second cost and the third cost is greater than thefourth cost, the splitting direction for the first partition isdetermined to be a direction from the top-right corner to thebottom-left corner. At this time, the second motion vector is selectedfor the second partition, and the first motion vector is assigned to thethird partition.

In the example illustrated in (c) of FIG. 24 , when the first cost isless than or equal to the second cost and the third cost is greater thanthe fourth cost, the splitting direction for the first partition isdetermined to be a direction from the top-left corner to thebottom-right corner. At this time, the first motion vector is selectedfor the second partition, and the second motion vector is assigned tothe third partition.

In the example illustrated in (d) of FIG. 24 , when the first cost isgreater than the second cost and the third cost is greater than or equalto the fourth cost, the splitting direction for the first partition isdetermined to be a direction from the top-right corner to thebottom-left corner. At this time, the first motion vector is selectedfor the third partition, and the second motion vector is assigned to thesecond partition.

Next, the examples illustrated in FIG. 25 are to be described. The firstpartitions are each split into two rectangular partitions in FIG. 25 .

In the example illustrated in (a) of FIG. 25 , when the first cost isless than or equal to the third cost and the first cost is less than orequal to the second cost, the splitting direction for the firstpartition is determined to be horizontal. At this time, the first motionvector is selected for the second partition, and the second motionvector is assigned to the third partition.

In the example illustrated in (b) of FIG. 25 , when the second cost isless than or equal to the fourth cost and the first cost is greater thanthe second cost, the splitting direction for the first partition isdetermined to be horizontal. At this time, the second motion vector isselected for the second partition, and the first motion vector isassigned to the third partition.

In the example illustrated in (c) of FIG. 25 , when the first cost isgreater than the third cost and the third cost is less than or equal tothe fourth cost, the splitting direction for the first partition isdetermined to be vertical. At this time, the first motion vector isselected for the second partition, and the second motion vector isassigned to the third partition.

In the example illustrated in (d) of FIG. 25 , when the second cost isgreater than the fourth cost and the third cost is greater than thefourth cost, the splitting direction for the first partition isdetermined to be vertical. At this time, the first motion vector isselected for the third partition, and the second motion vector isassigned to the second partition.

Next, in step S5005, the first partition is encoded or decoded using thesplitting direction determined in step S5003, and the at least twomotion vectors obtained in step S5001. Encoding the first partition mayinclude writing a parameter into a bitstream. Similarly, decoding thefirst partition may include reading a parameter from a bitstream.

FIG. 26 illustrates examples of parameters in the combined aspect. Asillustrated in FIG. 26 , in the combined aspect, the first motion vectorand the second motion vector are predicted from a motion vectorcandidate list, similarly to the second aspect. Specifically, aparameter may not indicate which of the first motion vector and thesecond motion vector indicates motion of the second partition and whichof the first motion vector and the second motion vector indicates motionof the third partition. As described in the first aspect, the splittingdirection for the first partition is calculated using costs, and thecosts are each calculated using at least two motion vectors.Accordingly, the parameters (parameter values in FIG. 26 ) may each beassociated with at least two motion vectors of the first partition. Thiseliminates the necessity of encoding or decoding assignment informationfor each of at least two motion vectors, and thus the encoding amountcan be reduced. For example, the combinations of two motion vectors forthe parameters in the second and third rows in FIG. 26 are the same asthe combination of two motion vectors for the parameter in the first row(parameter value of 0). Accordingly, conditions for the parameters inthe second and third rows are determined to be the same as the conditionfor the parameter in the first row, irrespective of whether thesplitting direction for the first partition is the same as that for theparameter in the first row. Thus, the parameters in the second and thirdrows are eliminated.

The above has given a description of examples in which motion vectorsare used as at least two items of prediction information when the secondpartition and the third partition are inter-predicted in the combinedaspect of the first aspect and the second aspect, yet the presentdisclosure is not limited to these. For example, the at least two itemsof prediction information may be merge candidates.

For example, when the second partition and the third partition areintra-predicted, the at least two items of prediction information may bemerge candidates or may be intra prediction modes.

FIG. 27 is a flowchart illustrating an example of intra predictionprocessing when the first aspect and the second aspect are combined. Asillustrated in FIG. 27 , in step S6001, at least two intra predictionmodes including the first intra prediction mode and the second intraprediction mode for the first partition are obtained.

Next, in step S6002, at least two costs for the first template and thesecond template are calculated using the at least two intra predictionmodes obtained in step S6001. Note that calculation of costs is asdescribed in the example of inter prediction processing described above.

Next, in step S6003, the splitting direction for the first partition isdetermined using the at least two costs calculated in step S6002.

Next, using the at least two costs calculated in step S6002, one of theat least two intra prediction modes is assigned to the second partition,and another of the at least two intra prediction modes is assigned tothe third partition.

Next, in step S6005, the first partition is encoded or decoded using thesplitting direction calculated in step S6003 and the intra predictionmode obtained in step S6001. At this time, the parameter may beassociated with the splitting direction for the first partition and theat least two intra prediction modes.

As described above, costs are used to determine a splitting directionfor the first partition and motion vectors of the second partition andthe third partition which are split from the first partition accordingto the splitting direction.

Thus, the term “motion vector” used in the description of the secondpartition and the third partition which are inter-predicted can bereplaced with the term “intra prediction mode” when the second partitionand the third partition are intra-predicted.

Third Aspect

This aspect introduces hardware implementation for using template costsin order to determine a splitting direction for the first partition orselect motion vectors for the third and fourth partitions. Note that thethird and fourth partitions in this aspect correspond to the secondpartition and the third partition in the first aspect and the secondaspect, respectively.

FIG. 28 is a flowchart illustrating an example of inter predictionprocessing in the third aspect. As illustrated in FIG. 28 , in stepS7001, at least two motion vectors including the first motion vector andthe second motion vector of the first partition are obtained.

Next, the second partition is obtained in step S7002. Note that thesecond partition in this aspect is different from the second partitionsin the first aspect and the second aspect. The second partitions in thefirst aspect and the second aspect are each split and derived from thefirst partition. Accordingly, the second partition is smaller than thefirst partition. On the other hand, the second partition in this aspectis not a partition split from the first partition.

FIG. 29 illustrates an example of the second partition in the thirdaspect. As illustrated in FIG. 29 , the second partition in this aspectis derived from the first partition and a plurality of neighboringsamples which neighbor the first partition. Accordingly, the secondpartition is larger than the first partition.

Next, in step S7003, at least two prediction blocks including a firstprediction block and a second prediction block of the second partitionare predicted using the at least two motion vectors obtained in stepS7001. For example, the first prediction block is predicted using thefirst motion vector for the second partition. For example, the secondprediction block is predicted using the second motion vector for thesecond partition.

Next, in step S7004, at least two costs are calculated using the atleast two prediction blocks of the second partition predicted in stepS7003 and the second partition. The following specifically describescalculation of costs, with reference to FIG. 30 .

FIG. 30 illustrates an example of calculation of costs in the thirdaspect. In FIG. 30 , (a) illustrates a relation between the secondpartition and the first and second templates which neighbor the firstpartition. In this example, the first template and the second templateare included in the second partition. The first template and the secondtemplate are derived from a plurality of neighboring samples whichneighbor the first partition.

In FIG. 30 , (b) illustrates an example of calculation of costs. In thisexample, four costs are calculated using the first and second templatesand first and second prediction blocks of the second partition.Specifically, a first cost is calculated using the first template andthe first prediction block, and a second cost is calculated using thefirst template and the second prediction block. A third cost iscalculated using the second template and the first prediction block, anda fourth cost is calculated using the second template and the secondprediction block.

As illustrated in (c) of FIG. 30 , the first cost is a cost between aplurality of reconstructed samples in the first template of the secondpartition and a plurality of prediction samples in the first template ofthe first prediction block. The second cost is a cost between aplurality of reconstructed samples in the first template of the secondpartition and a plurality of prediction samples in the first template ofthe second prediction block. The third cost is a cost between aplurality of reconstructed samples in the second template of the secondpartition and a plurality of prediction samples in the second templateof the first prediction block. The fourth cost is a cost between aplurality of reconstructed samples in the second template of the secondpartition and a plurality of prediction samples in the second templateof the second prediction block.

Next, in step S7005, the splitting direction for the first partition isdetermined using the at least two costs calculated in step S7004.

Next, in step S7006, the third partition is predicted from one of the atleast two prediction blocks predicted in step S7003, and the fourthpartition is predicted from another of the at least two predictionblocks. At this time, at least two costs are used to select predictionblocks for the third partition and the fourth partition which are splitfrom the first partition. Specifically, in processing in steps S7005 andS7006, the splitting direction for the first partition is determinedusing the at least two costs, and furthermore, prediction blocks for thethird partition and the fourth partition are selected using the at leasttwo costs.

The following more specifically describes the processing in steps S7005and S7006, with reference to FIGS. 31 and 32 . FIG. 31 illustrates anexample of processing in steps S7005 and S7006 in FIG. 28 . FIG. 32illustrates other examples of processing in steps S7005 and S7006 inFIG. 28 .

First, the examples illustrated in FIG. 31 are to be described. Thefirst partition is split into two triangular partitions in FIG. 31 .

In the example illustrated in (a) of FIG. 31 , when the first cost isless than or equal to the second cost and the third cost is less than orequal to the fourth cost, the splitting direction for the firstpartition is determined to be a direction from the top-right corner tothe bottom-left corner. At this time, the third partition is predictedfrom the first prediction block, and the fourth partition is predictedfrom the second prediction block.

In the example illustrated in (b) of FIG. 31 , when the first cost isgreater than the second cost and the third cost is greater than thefourth cost, the splitting direction for the first partition isdetermined to be a direction from the top-right corner to thebottom-left corner. At this time, the third partition is predicted fromthe second prediction block, and the fourth partition is predicted fromthe first prediction block.

In the example illustrated in (c) of FIG. 31 , when the first cost isless than or equal to the second cost and the third cost is greater thanthe fourth cost, the third partition is predicted from the firstprediction block, and the fourth partition is predicted from the secondprediction block.

In the example illustrated in (d) of FIG. 31 , when the first cost isgreater than the second cost and the third cost is less than or equal tothe fourth cost, the third partition is predicted from the secondprediction block, and the fourth partition is predicted from the firstprediction block.

Next, the examples illustrated in FIG. 32 are to be described. The firstpartition is split into two rectangular partitions in FIG. 32 .

In the example illustrated in (a) of FIG. 32 , when the first cost isless than or equal to the third cost and the first cost is less than orequal to the second cost, the splitting direction for the firstpartition is determined to be horizontal. At this time, the thirdpartition is predicted from the first prediction block, and the fourthpartition is predicted from the second prediction block.

In the example illustrated in (b) of FIG. 32 , when the second cost isless than or equal to the fourth cost and the first cost is greater thanthe second cost, the splitting direction for the first partition isdetermined to be horizontal. At this time, the third partition ispredicted from the second prediction block, and the fourth partition ispredicted from the first prediction block.

In the example illustrated in (c) of FIG. 32 , when the first cost isgreater than the third cost and the third cost is less than or equal tothe fourth cost, the splitting direction for the first partition isdetermined to be vertical. At this time, the third partition ispredicted from the first prediction block, and the fourth partition ispredicted from the second prediction block.

In the example illustrated in (d) of FIG. 32 , when the second cost isgreater than the fourth cost and the third cost is greater than thefourth cost, the splitting direction for the first partition isdetermined to be vertical. At this time, the third partition ispredicted from the second prediction block, and the fourth partition ispredicted from the first prediction block.

Next, in step S7007, the first partition is encoded or decoded using thesplitting direction for the first partition determined in step S7005,and the results of prediction of the third partition and the fourthpartition in step 7006. Encoding the first partition may include writinga parameter into a bitstream. Similarly, decoding the first partitionmay include reading a parameter from a bitstream.

The following describes an example of the case where inter predictionprocessing is performed on the first partition without applying thisaspect, and an example of the case where inter prediction processing isperformed on the first partition with the application of this aspect.

FIG. 33 illustrates an example of processing when the first partition isinter-predicted without applying the third aspect. In FIG. 33 , (a)illustrates the first partition, a first template derived from aplurality of upper neighboring samples located above the firstpartition, and a second template derived from a plurality of leftneighboring samples located on the left of the first partition.

As illustrated in (b) of FIG. 33 , the first template is predicted usingthe first motion vector. Further, the first template is predicted usingthe second motion vector. Similarly, the second template is predictedusing the first motion vector. Further, the second template is predictedusing the second motion vector.

In (c) of FIG. 33 , eight costs are calculated, using the first motionvector and the second motion vector of the first partition for each ofthe four templates derived in (b) of FIG. 33 .

As illustrated in (d) of FIG. 33 , using the costs calculated in (c) ofFIG. 33 , the splitting direction for the first partition and motionvector information for the third partition and the fourth partitionsplit from the first partition according to the splitting direction aredetermined.

As illustrated in (e) of FIG. 33 , the third partition and the fourthpartition are predicted based on the splitting direction and the motionvector information determined in (d) of FIG. 33 .

The first partition is encoded or decoded as illustrated in (f) of FIG.33 .

FIG. 34 illustrates examples of processing when the first partition isinter-predicted with the application of the third aspect. In FIG. 34 ,(a) illustrates a first partition, a first template derived from aplurality of upper neighboring samples located above the firstpartition, a second template derived from a plurality of leftneighboring samples located on the left of the first partition, and asecond partition derived from the first partition and a plurality ofneighboring samples which neighbor the first partition.

As illustrated in (b) of FIG. 34 , a first prediction block and a secondprediction block for the second partition are predicted using the firstmotion vector and the second motion vector.

In (c) of FIG. 34 , four costs are calculated, using the firstprediction block and the second prediction block of the second partitionfor each of the first template and the second template.

As illustrated in (d) of FIG. 34 , a splitting direction for the firstpartition, and motion vector information for the third partition and thefourth partition which are split from the first partition according tothe splitting direction are determined, using the costs calculated in(c) of FIG. 34 .

The first partition is encoded or decoded as illustrated in (e) of FIG.34 .

As described above, if inter prediction processing is performed on thefirst partition without applying this aspect, the number of templates tobe derived, the number of costs to be calculated, the number ofprocesses to be performed, and the encoding amount increase.

In contrast, if the first partition is inter-predicted with theapplication of this aspect, the number of templates to be derived, thenumber of costs to be calculated, the number of processes to beperformed, and the encoding amount are reduced.

Technical Advantages of Third Aspect

This aspect introduces a hardware implementation method for usingtemplate costs to determine the splitting direction and motion vectorinformation for a partition. According to this aspect, it needs toaccess memory only once to predict the partition, using a largerpartition for each motion vector. Accordingly, the processing time topredict the partition can be shortened.

Combination With Other Aspects

At least a portion of the third aspect may be combined with at least aportion of one or more other aspects of the present disclosure. Aportion of processing in the flowcharts, a configuration of a portion ofa device, syntax, and/or other features may be combined with otheraspects. Not all the above processing/elements are necessarily needed.The device/method may include a portion of the processing/one or more ofthe elements. The processing described above may be performed by adecoder, similarly to the encoder.

Fourth Aspect

In this aspect, at least two costs are used to determine a splittingdirection for the first partition, and motion vectors of the secondpartition and the third partition which are split from the firstpartition according to the splitting direction. At least two costs arecalculated using two prediction partitions predicted from at least tworeference frames of the first partition.

FIG. 35 is a flowchart illustrating an example of inter predictionprocessing in the fourth aspect.

As illustrated in FIG. 35 , in step S8001, at least two motion vectorsincluding the first motion vector and the second motion vector of thefirst partition are obtained. The first motion vector may be aunidirectional motion vector predictor or a bidirectional motion vectorpredictor. Similarly, the second motion vector may be a unidirectionalmotion vector predictor or a bidirectional motion vector predictor.

Next, in step S8002, at least two costs are calculated for the firstpartition using the at least two motion vectors. In this example, the atleast two costs are calculated using at least two prediction partitionspredicted from at least two reference frames of the first partition.

FIG. 36 illustrates an example of obtaining at least two predictionpartitions (PredO, Pred1) for the first partition, using the firstmotion vector.

The first partition is located in a current frame as illustrated in FIG.36 . The at least two prediction partitions (PredO, Pred1) are predictedfrom two reference frames (Ref0, Ref1). For example, if a first motionvector (MV1) is a unidirectional motion vector predictor and points toreference frame 0 (Ref0), a mirrored motion vector (MV1′) is derivedfrom MV1 along the motion trajectory, pointing to reference frame 1(Ref1). On the other hand, when the first motion vector is abidirectional motion vector predictor, the two first motion vectors (MV1and MV1′) point to reference frame 0 (Ref0) and reference frame 1(Ref1), respectively.

FIG. 37 illustrates an example in which at least two predictionpartitions (Pred2, Pred3) are obtained for the first partition, usingthe second motion vector. Also for the second motion vector, the firstpartition is located in a current frame, similarly. At least twoprediction partitions (Pred2, Pred3) are predicted from two referenceframes (Ref2, Ref3). For example, when the second motion vector (MV2) isa unidirectional motion vector predictor and points to reference frame 2(Ref2), a mirrored motion vector (MV2′) is derived from MV2 along themotion trajectory, pointing to reference frame 3 (Ref3). On the otherhand, when the second motion vector is a bidirectional motion vectorpredictor, the two second motion vector predictors (MV1, MV2′) point toreference frame 2 (Ref2) and reference frame 3 (Ref3), respectively.

Next, an example of calculation of costs in this aspect is to bedescribed. FIG. 38A illustrates examples of calculation of costs in thefourth aspect. FIG. 38B illustrates other examples of calculation ofcosts in the fourth aspect.

First, examples illustrated in FIG. 38A are to be described. Asillustrated in (a) of FIG. 38A, four prediction partitions (PredO,Pred1, Pred2, Pred3) are predicted for the first partition, using thefirst motion vector and the second motion vector. Next, as illustratedin (b) of FIG. 38A, 16 prediction partitions are derived from the fourprediction partitions. The 16 prediction partitions are triangularpartitions. Next, as illustrated in (c) of FIG. 38A, costs arecalculated using the derived 16 prediction partitions. A first cost is asum of a cost between Pred000 and Pred100 and a cost between Pred201 andPred301. A second cost is a sum of a cost between Pred001 and Pred101and a cost between Pred200 and Pred300. A third cost is a sum of a costbetween Pred010 and Pred110 and a cost between Pred211 and Pred311. Afourth cost is a sum of a cost between Pred011 and Pred111 and a costbetween Pred210 and Pred310.

Next, the examples illustrated in FIG. 38B are to be described. Asillustrated in (a) of FIG. 38B, four prediction partitions (PredO,Pred1, Pred2, Pred3) are predicted for the first partition, using thefirst motion vector and the second motion vector. Next, as illustratedin (b) of FIG. 38B, 16 prediction partitions are derived from the fourprediction partitions. 16 prediction partitions are rectangularpartitions. Next, as illustrated in (c) of FIG. 38B, costs arecalculated using the derived 16 prediction partitions. A first cost is asum of a cost between Pred000 and Pred100 and a cost between Pred201 andPred301. A second cost is a sum of a cost between Pred001 and Pred101and a cost between Pred200 and Pred300. A third cost is a sum of a costbetween Pred010 and Pred110 and a cost between Pred211 and Pred311. Afourth cost is a sum of a cost between Pred011 and Pred111 and a costbetween Pred210 and Pred310.

Next, in step S8003, a splitting direction for the first partition isdetermined using the at least two costs calculated in step S8002. Thefirst partition is split into the second partition and the thirdpartition along the splitting direction.

Next, in step S8004, one of at least two motion vectors is assigned tothe second partition and another of the at least two motion vectors isassigned to the third partition, using the at least two costs calculatedin step S8002. Note that the motion vector assigned to the secondpartition is different from the motion vector assigned to the thirdpartition.

The following more specifically describes the processing in steps S8003and S8004 with reference to FIGS. 39A and 39B. FIG. 39A illustratesexamples of processing in steps S8003 and S8004 in FIG. 35 . FIG. 39Billustrates other examples of processing in steps S8003 and S8004 inFIG. 35 .

First, the examples illustrated in FIG. 39A are to be described. Thefirst partition is split into two triangular partitions in FIG. 39A.

In the example illustrated in (a) of FIG. 39A, when the minimum cost isthe first cost, the splitting direction for the first partition isdetermined to be a direction from the top-right corner to thebottom-left corner. At this time, the first motion vector is assigned tothe second partition and the second motion vector is assigned to thethird partition.

In the example illustrated in (b) of FIG. 39A, when the minimum cost isthe second cost, the splitting direction for the first partition isdetermined to be a direction from the top-right corner to thebottom-left corner. At this time, the second motion vector is assignedto the second partition, and the first motion vector is assigned to thethird partition.

In the example illustrated in (c) of FIG. 39A, when the minimum cost isthe third cost, the splitting direction for the first partition isdetermined to be a direction from the top-left corner to thebottom-right corner. At this time, the first motion vector is assignedto the second partition, and the second motion vector is assigned to thethird partition.

In the example illustrated in (d) of FIG. 39A, when the minimum cost isthe fourth cost, the splitting direction for the first partition isdetermined to be a direction from the top-left corner to thebottom-right corner. At this time, the second motion vector is assignedto the second partition, and the first motion vector is assigned to thethird partition.

Next, the example illustrated in FIG. 39B is to be described. The firstpartition is split into two rectangular partitions in FIG. 39B.

In the example illustrated in (a) of FIG. 39B, when the minimum cost isthe first cost, the splitting direction for the first partition isdetermined to be horizontal. At this time, the first motion vector isassigned to the second partition, and the second motion vector isassigned to the third partition.

In the example illustrated in (b) of FIG. 39B, when the minimum cost isthe second cost, the splitting direction for the first partition isdetermined to be horizontal. At this time, the second motion vector isassigned to the second partition, and the first motion vector isassigned to the third partition.

In the example illustrated in (c) of FIG. 39B, when the minimum cost isthe third cost, the splitting direction for the first partition isvertical. At this time, the first motion vector is assigned to thesecond partition, and the second motion vector is assigned to the thirdpartition.

In the example illustrated in (d) of FIG. 39B, when the minimum cost isthe fourth cost, the splitting direction for the first partition isdetermined to be vertical. At this time, the second motion vector isassigned to the second partition, and the first motion vector isassigned to the third partition.

Next, in step S8005, the first partition is encoded or decoded using thesplitting direction determined in step S8003 and the at least two motionvectors obtained in step S8001.

Technical Advantage of Fourth Aspect

This aspect introduces costs in order to determine the splittingdirection for the first partition and the motion vectors of the secondpartition and the third partition which are split from the firstpartition. Costs are calculated using at least two prediction partitionspredicted from at least two reference frames of the first partition.According to this aspect, the splitting direction of the first partitionis not transmitted. Further, the motion vectors for the second partitionand the third partition are jointly encoded without indicating whichmotion vector is for the second partition and which motion vector is forthe third partition. According to this aspect, encoding efficiency canbe improved.

Combination With Other Aspects

At least of a portion of the fourth aspect may be combined with at leasta portion of one or more other aspects of the present disclosure. Aportion of processing in the flowcharts, a configuration of a portion ofa device, syntax and/or other features may be combined with otheraspects. Not all the above processing/elements are necessarily needed.The device/method may include a portion of the processing/one or more ofthe elements. The processing described above may be performed by adecoder, similarly to the encoder. In an example, step S1002 in FIG. 11may be replaced with step S8002 in FIG. 35 . In another example, stepS3003 in FIG. 18 may be replaced with step S8002 in FIG. 35 .

Variation

The first partition split into the second partition and the thirdpartition may be a rectangular partition, a triangular partition, or anon-rectangular partition. The first partition may be split into aplurality of partitions which at least include the second partition andthe third partition. The term “partition” described in each aspect maybe replaced with the term “coding unit”. The term “partition” describedin each aspect may be replaced with the term “prediction unit”. The term“partition” described in each aspect may be replaced with the term “subprediction unit”.

Example of Implementation of Encoder

FIG. 40 is a block diagram illustrating an example of implementation ofencoder 100 according to Embodiment 1. Encoder 100 includes circuitry160 and memory 162. For example, the plurality of elements of encoder100 illustrated in FIG. 1 are implemented by circuitry 160 and memory162 which are illustrated in FIG. 40 .

Circuitry 160 is an electronic circuit accessible to memory 162, andprocesses information. For example, circuitry 160 is a dedicated orgeneral-purpose circuitry which encodes videos using memory 162.Circuitry 160 may be a central processing unit (CPU).

Circuitry 160 may be constituted by a plurality of electronic circuitsor by a plurality of sub circuits. Among the plurality of elements ofencoder 100 illustrated in FIG. 1 , circuitry 160 may serve as aplurality of elements, other than the elements for storing information.

Memory 162 is a dedicated or general-purpose memory which storesinformation for circuitry 160 to encode videos. Memory 162 may be anelectronic circuit, may be connected to circuitry 160, or may beincluded in circuitry 160.

Memory 162 may be constituted by a plurality of electronic circuits orby a plurality of sub circuits. Memory 162 may be a magnetic disk or anoptical disc, for instance, and may be expressed as storage or arecording medium. Memory 162 may be nonvolatile memory or volatilememory.

For example, memory 162 may serve as elements for storing information,among the plurality of elements of encoder 100 illustrated in FIG. 1 .Specifically, memory 162 may serve as block memory 118 and frame memory122 illustrated in FIG. 1 .

Further, memory 162 may store videos to be encoded, and bit stringscorresponding to the encoded videos. Further, memory 162 may store aprogram for circuitry 160 to encode videos.

Encoder 100 may not be provided with all the plurality of elementsillustrated in FIG. 1 , and may not perform all the processes describedabove. One or more of the plurality of elements illustrated in FIG. 1may be included in another device, or one or more of the plurality ofprocesses described above may be performed by the other device. Encoder100 is provided with one or more of the plurality of elementsillustrated in FIG. 1 and performs one or more of the plurality ofprocesses described above, thus inhibiting an increase in the amount ofprocessing and adaptively determining information related to splittingbased on the characteristics of neighboring samples.

As described above, circuitry 160 of encoder 100 illustrated in FIG. 40encodes videos using memory 162 of encoder 100.

For example, circuitry 160 obtains at least two items of predictioninformation for a first partition included in an image which a videoincludes. Circuitry 160 derives at least one template from a pluralityof neighboring samples which neighbor the first partition. Circuitry 160calculates at least two costs using at least one template and the atleast two items of prediction information. Using the at least two costs,circuitry 160 (i) determines at least one splitting direction for thefirst partition, or (ii) assigns one of the at least two items ofprediction information to a second partition split from the firstpartition according to the at least one splitting direction, and anotherof the at least two items of prediction information to a third partitionsplit from the first partition according to the at least one splittingdirection. Then, circuitry 160 encodes the first partition according tothe at least one splitting direction and the at least two items ofprediction information.

For example, the plurality of neighboring samples which neighbor thefirst partition may be a plurality of neighboring samples whichtemporally or spatially neighbor the first partition.

For example, the at least two items of prediction information may bemotion vectors, merge candidates, or intra prediction modes.

For example, the at least one template may include, among the pluralityof neighboring samples, a template derived from an upper neighboringsample located above the first partition, a template derived from a leftneighboring sample located on the left of the first partition, or atemplate derived from the upper neighboring sample and a templatederived from the left neighboring sample.

For example, calculation of the at least two costs may include at leasta minus operation.

For example, the second partition and the third partition may betriangular partitions or rectangular partitions.

For example, the at least one splitting direction may be a directionfrom the top-left corner to the bottom-right corner of the firstpartition, a direction from the top-right corner to the bottom-leftcorner of the first partition, horizontal, or vertical.

For example, the at least two items of prediction information includesfirst prediction information, and second prediction informationdifferent from the first prediction information, and the firstprediction information and the second prediction information may beobtained for the second partition and the third partition in the firstpartition.

For example, using at least two costs, circuitry 160 may (i) determineat least one splitting direction for the first partition, and (ii)assign one of the at least two items of prediction information to thesecond partition and another of the at least two items of predictioninformation to the third partition.

For example, the at least two costs may be calculated, using at leasttwo prediction partitions predicted from at least two reference framesof the first partition using the at least two items of predictioninformation.

Note that encoder 100 is not limited to the above example ofimplementation, and may include subtractor 104, transformer 106,quantizer 108, and entropy encoder 110. These elements may perform theabove operation.

Example of Implementation of Decoder

FIG. 41 is a block diagram illustrating an example of implementation ofdecoder 200 according to Embodiment 1. Decoder 200 includes circuitry260 and memory 262. For example, the plurality of elements of decoder200 illustrated in FIG. 10 are implemented by circuitry 260 and memory262 which are illustrated in FIG. 41 .

Circuitry 260 is an electronic circuit accessible to memory 262, andprocesses information. For example, circuitry 260 is a dedicated orgeneral-purpose circuitry which decodes videos using memory 262.Circuitry 260 may be a CPU.

Circuitry 260 may be constituted by a plurality of electronic circuits,or may be constituted by a plurality of sub circuits. Among theplurality of elements of decoder 200 illustrated in FIG. 10 , circuitry260 may serve as a plurality of elements, other than the elements forstoring information.

Memory 262 is a dedicated or general-purpose memory which storesinformation for circuitry 260 to decode videos. Memory 262 may be anelectronic circuit, may be connected to circuitry 260, or may beincluded in circuitry 260.

Memory 262 may be constituted by a plurality of electronic circuits ormay be constituted by a plurality of sub circuits. Memory 262 may be amagnetic disk or an optical disc or may be expressed as storage or arecording medium. Memory 262 may be nonvolatile memory or volatilememory.

For example, memory 262 may serve as elements for storing information,among the plurality of elements of decoder 200 illustrated in FIG. 10 .Specifically, memory 262 may serve as block memory 210 and frame memory214 illustrated in FIG. 10 .

Memory 262 may store bit strings corresponding to encoded videos, andvideos corresponding to decoded bit strings. Further, memory 262 maystore a program for circuitry 260 to decode videos.

Decoder 200 may not be provided with all the plurality of elementsillustrated in FIG. 10 , or may not perform all the plurality ofprocesses described above. One or more of the plurality of elementsillustrated in FIG. 10 may be included in another device, and one ormore of the plurality of processes described above may be performed bythe other device. Decoder 200 is provided with one or more of theplurality of elements illustrated in FIG. 10 and performs one or more ofthe plurality of processes described above, thus inhibiting an increasein the amount of processing and adaptively determining informationrelated to splitting, based on characteristics of neighboring samples.

As described above, circuitry 260 of decoder 200 illustrated in FIG. 41decodes videos using memory 262 of decoder 200.

For example, circuitry 260 obtains at least two items of predictioninformation for a first partition included in an image which a videoincludes. Circuitry 260 derives at least one template from a pluralityof neighboring samples which neighbor the first partition. Circuitry 260calculates at least two costs using the at least one template and the atleast two items of prediction information. Using the at least two costs,circuitry 260 (i) determines at least one splitting direction for thefirst partition, or (ii) assigns one of the at least two items ofprediction information to a second partition split from the firstpartition according to the at least one splitting direction, and anotherof the at least two items of prediction information to a third partitionsplit from the first partition according to the at least one splittingdirection. Then, circuitry 260 decodes the first partition according tothe at least one splitting direction and the at least two items ofprediction information.

For example, the plurality of neighboring samples which neighbor thefirst partition may be a plurality of neighboring samples whichtemporally or spatially neighbor the first partition.

For example, the at least two items of prediction information may bemotion vectors, merge candidates, or intra prediction modes.

For example, the at least one template may include, among the pluralityof neighboring samples, a template derived from an upper neighboringsample located above the first partition, may include a template derivedfrom a left neighboring sample located on the left of the firstpartition, or may include a template derived from the upper neighboringsample and a template derived from the left neighboring sample.

For example, calculation of the at least two costs may include at leasta minus operation.

For example, the second partition and the third partition may betriangular partitions or rectangular partitions.

For example, the at least one splitting direction may be a directionfrom a top-left corner to a bottom-right corner of the first partition,a direction from a top-right corner to a bottom-left corner of the firstpartition, horizontal, or vertical.

For example, the at least two items of prediction information mayinclude first prediction information and second prediction informationdifferent from the first prediction information, and the firstprediction information and the second prediction information may beobtained for the second partition and the third partition in the firstpartition.

For example, using the at least two costs, circuitry 260 may (i)determine at least one splitting direction for the first partition, and(ii) assign one of the at least two items of prediction information tothe second partition, and another of the at least two items ofprediction information to the third partition.

For example, the at least two costs may be calculated, using at leasttwo prediction partitions predicted from at least two reference framesof the first partition using at least two items of predictioninformation.

Note that decoder 200 is not limited to the above example ofimplementation, and may include entropy decoder 202, inverse quantizer204, inverse transformer 206, and adder 208. These elements may performthe above operation.

Supplement

Encoder 100 and decoder 200 according to the present embodiment may beused as an image encoder and an image decoder, respectively, or may beused as a video encoder and a video decoder, respectively.Alternatively, encoder 100 and decoder 200 may be each used as atransformer.

Accordingly, encoder 100 and decoder 200 may correspond only totransformer 106 and inverse transformer 206, respectively. Then, otherelements such as inter predictor 126 or 218 may be included in anotherdevice.

At least a portion of the present embodiment may be used as an encodingmethod, may be used as a decoding method, may be used as a transformingmethod, or may be used as another method.

In the present embodiment, each of the elements may be configured ofdedicated hardware, or may be implemented by executing a softwareprogram suitable for the element. Each element may be implemented by aprogram executor such as a CPU or a processor reading and executing asoftware program recorded on a recording medium such as a hard disk orsemiconductor memory.

Specifically, each of encoder 100 and decoder 200 may include processingcircuitry, and storage electrically coupled to the processing circuitryand accessible from the processing circuitry. For example, theprocessing circuitry corresponds to circuitry 160 or 260, and thestorage corresponds to memory 162 or 262.

The processing circuitry includes at least one of dedicated hardware anda program executor, and performs a process using the storage. When theprocessing circuitry includes a program executor, the storage stores asoftware program executed by the program executor.

Here, software which implements, for instance, encoder 100 or decoder200 according to the present embodiment is a program as follows.

Thus, this program causes a computer to perform an encoding method forencoding a video, the encoding method including: obtaining at least twoitems of prediction information for a first partition included in thevideo; deriving at least one template from a plurality of neighboringsamples which neighbor the first partition; calculating at least twocosts, using the at least one template and the at least two items ofprediction information; (i) determining at least one splitting directionfor the first partition, using the at least two costs or (ii) assigning,using the at least two costs, one of the at least two items ofprediction information to a second partition split from the firstpartition according to the at least one splitting direction, and anotherof the at least two items of prediction information to a third partitionsplit from the first partition according to the at least one splittingdirection; and encoding the first partition according to the at leastone splitting direction and the at least two items of predictioninformation.

Alternatively, this program causes a computer to perform a decodingmethod for decoding a video, the decoding method including: obtaining atleast two items of prediction information for a first partition includedin the video; deriving at least one template from a plurality ofneighboring samples which neighbor the first partition; calculating atleast two costs, using the at least one template and the at least twoitems of prediction information; (i) determining at least one splittingdirection for the first partition, using the at least two costs or (ii)assigning, using the at least two costs, one of the at least two itemsof prediction information to a second partition split from the firstpartition according to the at least one splitting direction, and anotherof the at least two items of prediction information to a third partitionsplit from the first partition according to the at least one splittingdirection; and decoding the first partition according to the at leastone splitting direction and the at least two items of predictioninformation.

The elements may be circuits as above-mentioned. These circuits mayconstitute one circuitry as a whole, or may be separate circuitries.Each element may be implemented by a general-purpose processor or adedicated processor.

A process performed by a specific element may be performed by adifferent element. In addition, the order of performing processes may bechanged or the plurality of processes may be performed in parallel. Theencoder/decoder may include encoder 100 and decoder 200.

The ordinal numbers such as first and second used for the descriptionmay be changed properly. An ordinal number may be newly given to anelement or may be removed therefrom.

The above has given a description of aspects of encoder 100 and decoder200 based on the embodiments, but the aspects are not limited to theembodiments. The aspects of encoder 100 and decoder 200 may alsoencompass various modifications that may be conceived by those skilledin the art to the embodiments, and embodiments achieved by combiningelements in different embodiments, without departing from the scope ofthe present disclosure.

This aspect may be implemented in combination with one or more of theother aspects according to the present disclosure. In addition, part ofthe processes in the flowcharts, part of the constituent elements of theapparatuses, and part of the syntax described in this aspect may beimplemented in combination with other aspects.

Embodiment 2

As described in each of the above embodiments, each functional block cantypically be realized as an MPU and memory, for example. Moreover,processes performed by each of the functional blocks are typicallyrealized by a program execution unit, such as a processor, reading andexecuting software (a program) recorded on a recording medium such asROM. The software may be distributed via, for example, downloading, andmay be recorded on a recording medium such as semiconductor memory anddistributed. Note that each functional block can, of course, also berealized as hardware (dedicated circuit).

Moreover, the processing described in each of the embodiments may berealized via integrated processing using a single apparatus (system),and, alternatively, may be realized via decentralized processing using aplurality of apparatuses. Moreover, the processor that executes theabove-described program may be a single processor or a plurality ofprocessors. In other words, integrated processing may be performed, and,alternatively, decentralized processing may be performed.

Embodiments of the present disclosure are not limited to the aboveexemplary embodiments; various modifications may be made to theexemplary embodiments, the results of which are also included within thescope of the embodiments of the present disclosure.

Next, application examples of the moving picture encoding method (imageencoding method) and the moving picture decoding method (image decodingmethod) described in each of the above embodiments and a system thatemploys the same will be described. The system is characterized asincluding an image encoder that employs the image encoding method, animage decoder that employs the image decoding method, and an imageencoder/decoder that includes both the image encoder and the imagedecoder. Other configurations included in the system may be modified ona case-by-case basis.

Usage Examples

FIG. 42 illustrates an overall configuration of content providing systemex 100 for implementing a content distribution service. The area inwhich the communication service is provided is divided into cells ofdesired sizes, and base stations ex 106, ex 107, ex 108, ex 109, and ex110, which are fixed wireless stations, are located in respective cells.

In content providing system ex 100, devices including computer ex 111,gaming device ex 112, camera ex 113, home appliance ex 114, andsmartphone ex 115 are connected to internet ex 101 via internet serviceprovider ex 102 or communications network ex 104 and base stations ex106 through ex 110. Content providing system ex 100 may combine andconnect any combination of the above elements. The devices may bedirectly or indirectly connected together via a telephone network ornear field communication rather than via base stations ex 106 through ex110, which are fixed wireless stations. Moreover, streaming server ex103 is connected to devices including computer ex 111, gaming device ex112, camera ex 113, home appliance ex 114, and smartphone ex 115 via,for example, internet ex 101. Streaming server ex 103 is also connectedto, for example, a terminal in a hotspot in airplane ex 117 viasatellite ex 116.

Note that instead of base stations ex 106 through ex 110, wirelessaccess points or hotspots may be used. Streaming server ex 103 may beconnected to communications network ex 104 directly instead of viainternet ex 101 or internet service provider ex 102, and may beconnected to airplane ex 117 directly instead of via satellite ex 116.

Camera ex 113 is a device capable of capturing still images and video,such as a digital camera. Smartphone ex 115 is a smartphone device,cellular phone, or personal handyphone system (PHS) phone that canoperate under the mobile communications system standards of the typical2G, 3G, 3.9G, and 4G systems, as well as the next-generation 5G system.

Home appliance ex 118 is, for example, a refrigerator or a deviceincluded in a home fuel cell cogeneration system.

In content providing system ex 100, a terminal including an image and/orvideo capturing function is capable of, for example, live streaming byconnecting to streaming server ex 103 via, for example, base station ex106. When live streaming, a terminal (e.g., computer ex 111, gamingdevice ex 112, camera ex 113, home appliance ex 114, smartphone ex 115,or airplane ex 117) performs the encoding processing described in theabove embodiments on still-image or video content captured by a user viathe terminal, multiplexes video data obtained via the encoding and audiodata obtained by encoding audio corresponding to the video, andtransmits the obtained data to streaming server ex 103. In other words,the terminal functions as the image encoder according to one aspect ofthe present disclosure.

Streaming server ex 103 streams transmitted content data to clients thatrequest the stream. Client examples include computer ex 111, gamingdevice ex 112, camera ex 113, home appliance ex 114, smartphone ex 115,and terminals inside airplane ex 117, which are capable of decoding theabove-described encoded data. Devices that receive the streamed datadecode and reproduce the received data. In other words, the devices eachfunction as the image decoder according to one aspect of the presentdisclosure.

Decentralized Processing

Streaming server ex 103 may be realized as a plurality of servers orcomputers between which tasks such as the processing, recording, andstreaming of data are divided. For example, streaming server ex 103 maybe realized as a content delivery network (CDN) that streams content viaa network connecting multiple edge servers located throughout the world.In a CDN, an edge server physically near the client is dynamicallyassigned to the client. Content is cached and streamed to the edgeserver to reduce load times. In the event of, for example, some kind ofan error or a change in connectivity due to, for example, a spike intraffic, it is possible to stream data stably at high speeds since it ispossible to avoid affected parts of the network by, for example,dividing the processing between a plurality of edge servers or switchingthe streaming duties to a different edge server, and continuingstreaming.

Decentralization is not limited to just the division of processing forstreaming; the encoding of the captured data may be divided between andperformed by the terminals, on the server side, or both. In one example,in typical encoding, the processing is performed in two loops. The firstloop is for detecting how complicated the image is on a frame-by-frameor scene-by-scene basis, or detecting the encoding load. The second loopis for processing that maintains image quality and improves encodingefficiency. For example, it is possible to reduce the processing load ofthe terminals and improve the quality and encoding efficiency of thecontent by having the terminals perform the first loop of the encodingand having the server side that received the content perform the secondloop of the encoding. In such a case, upon receipt of a decodingrequest, it is possible for the encoded data resulting from the firstloop performed by one terminal to be received and reproduced on anotherterminal in approximately real time. This makes it possible to realizesmooth, real-time streaming.

In another example, camera ex 113 or the like extracts a feature amountfrom an image, compresses data related to the feature amount asmetadata, and transmits the compressed metadata to a server. Forexample, the server determines the significance of an object based onthe feature amount and changes the quantization accuracy accordingly toperform compression suitable for the meaning of the image. Featureamount data is particularly effective in improving the precision andefficiency of motion vector prediction during the second compressionpass performed by the server. Moreover, encoding that has a relativelylow processing load, such as variable length coding (VLC), may behandled by the terminal, and encoding that has a relatively highprocessing load, such as context-adaptive binary arithmetic coding(CABAC), may be handled by the server.

In yet another example, there are instances in which a plurality ofvideos of approximately the same scene are captured by a plurality ofterminals in, for example, a stadium, shopping mall, or factory. In sucha case, for example, the encoding may be decentralized by dividingprocessing tasks between the plurality of terminals that captured thevideos and, if necessary, other terminals that did not capture thevideos and the server, on a per-unit basis. The units may be, forexample, groups of pictures (GOP), pictures, or tiles resulting fromdividing a picture. This makes it possible to reduce load times andachieve streaming that is closer to real-time.

Moreover, since the videos are of approximately the same scene,management and/or instruction may be carried out by the server so thatthe videos captured by the terminals can be cross-referenced. Moreover,the server may receive encoded data from the terminals, change referencerelationship between items of data or correct or replace picturesthemselves, and then perform the encoding. This makes it possible togenerate a stream with increased quality and efficiency for theindividual items of data.

Moreover, the server may stream video data after performing transcodingto convert the encoding format of the video data. For example, theserver may convert the encoding format from MPEG to VP, and may convertH.264 to H.265.

In this way, encoding can be performed by a terminal or one or moreservers. Accordingly, although the device that performs the encoding isreferred to as a “server” or “terminal” in the following description,some or all of the processes performed by the server may be performed bythe terminal, and likewise some or all of the processes performed by theterminal may be performed by the server. This also applies to decodingprocesses.

3D, Multi-Angle

In recent years, usage of images or videos combined from images orvideos of different scenes concurrently captured or the same scenecaptured from different angles by a plurality of terminals such ascamera ex 113 and/or smartphone ex 115 has increased. Videos captured bythe terminals are combined based on, for example, theseparately-obtained relative positional relationship between theterminals, or regions in a video having matching feature points.

In addition to the encoding of two-dimensional moving pictures, theserver may encode a still image based on scene analysis of a movingpicture either automatically or at a point in time specified by theuser, and transmit the encoded still image to a reception terminal.Furthermore, when the server can obtain the relative positionalrelationship between the video capturing terminals, in addition totwo-dimensional moving pictures, the server can generatethree-dimensional geometry of a scene based on video of the same scenecaptured from different angles. Note that the server may separatelyencode three-dimensional data generated from, for example, a pointcloud, and may, based on a result of recognizing or tracking a person orobject using three-dimensional data, select or reconstruct and generatea video to be transmitted to a reception terminal from videos capturedby a plurality of terminals.

This allows the user to enjoy a scene by freely selecting videoscorresponding to the video capturing terminals, and allows the user toenjoy the content obtained by extracting, from three-dimensional datareconstructed from a plurality of images or videos, a video from aselected viewpoint. Furthermore, similar to with video, sound may berecorded from relatively different angles, and the server may multiplex,with the video, audio from a specific angle or space in accordance withthe video, and transmit the result.

In recent years, content that is a composite of the real world and avirtual world, such as virtual reality (VR) and augmented reality (AR)content, has also become popular. In the case of VR images, the servermay create images from the viewpoints of both the left and right eyesand perform encoding that tolerates reference between the two viewpointimages, such as multi-view coding (MVC), and, alternatively, may encodethe images as separate streams without referencing. When the images aredecoded as separate streams, the streams may be synchronized whenreproduced so as to recreate a virtual three-dimensional space inaccordance with the viewpoint of the user.

In the case of AR images, the server superimposes virtual objectinformation existing in a virtual space onto camera informationrepresenting a real-world space, based on a three-dimensional positionor movement from the perspective of the user. The decoder may obtain orstore virtual object information and three-dimensional data, generatetwo-dimensional images based on movement from the perspective of theuser, and then generate superimposed data by seamlessly connecting theimages. Alternatively, the decoder may transmit, to the server, motionfrom the perspective of the user in addition to a request for virtualobject information, and the server may generate superimposed data basedon three-dimensional data stored in the server in accordance with thereceived motion, and encode and stream the generated superimposed datato the decoder. Note that superimposed data includes, in addition to RGBvalues, an α value indicating transparency, and the server sets the αvalue for sections other than the object generated fromthree-dimensional data to, for example, 0, and may perform the encodingwhile those sections are transparent. Alternatively, the server may setthe background to a predetermined RGB value, such as a chroma key, andgenerate data in which areas other than the object are set as thebackground.

Decoding of similarly streamed data may be performed by the client(i.e., the terminals), on the server side, or divided therebetween. Inone example, one terminal may transmit a reception request to a server,the requested content may be received and decoded by another terminal,and a decoded signal may be transmitted to a device having a display. Itis possible to reproduce high image quality data by decentralizingprocessing and appropriately selecting content regardless of theprocessing ability of the communications terminal itself. In yet anotherexample, while a TV, for example, is receiving image data that is largein size, a region of a picture, such as a tile obtained by dividing thepicture, may be decoded and displayed on a personal terminal orterminals of a viewer or viewers of the TV This makes it possible forthe viewers to share a big-picture view as well as for each viewer tocheck his or her assigned area or inspect a region in further detail upclose.

In the future, both indoors and outdoors, in situations in which aplurality of wireless connections are possible over near, mid, and fardistances, it is expected to be able to seamlessly receive content evenwhen switching to data appropriate for the current connection, using astreaming system standard such as MPEG-DASH. With this, the user canswitch between data in real time while freely selecting a decoder ordisplay apparatus including not only his or her own terminal, but also,for example, displays disposed indoors or outdoors. Moreover, based on,for example, information on the position of the user, decoding can beperformed while switching which terminal handles decoding and whichterminal handles the displaying of content. This makes it possible to,while in route to a destination, display, on the wall of a nearbybuilding in which a device capable of displaying content is embedded oron part of the ground, map information while on the move. Moreover, itis also possible to switch the bit rate of the received data based onthe accessibility to the encoded data on a network, such as when encodeddata is cached on a server quickly accessible from the receptionterminal or when encoded data is copied to an edge server in a contentdelivery service.

Scalable Encoding

The switching of content will be described with reference to a scalablestream, illustrated in FIG. 43 , that is compression coded viaimplementation of the moving picture encoding method described in theabove embodiments. The server may have a configuration in which contentis switched while making use of the temporal and/or spatial scalabilityof a stream, which is achieved by division into and encoding of layers,as illustrated in FIG. 43 . Note that there may be a plurality ofindividual streams that are of the same content but different quality.In other words, by determining which layer to decode up to based oninternal factors, such as the processing ability on the decoder side,and external factors, such as communication bandwidth, the decoder sidecan freely switch between low resolution content and high resolutioncontent while decoding. For example, in a case in which the user wantsto continue watching, at home on a device such as a TV connected to theinternet, a video that he or she had been previously watching onsmartphone ex 115 while on the move, the device can simply decode thesame stream up to a different layer, which reduces server side load.

Furthermore, in addition to the configuration described above in whichscalability is achieved as a result of the pictures being encoded perlayer and the enhancement layer is above the base layer, the enhancementlayer may include metadata based on, for example, statisticalinformation on the image, and the decoder side may generate high imagequality content by performing super-resolution imaging on a picture inthe base layer based on the metadata. Super-resolution imaging may beimproving the SN ratio while maintaining resolution and/or increasingresolution. Metadata includes information for identifying a linear or anon-linear filter coefficient used in super-resolution processing, orinformation identifying a parameter value in filter processing, machinelearning, or least squares method used in super-resolution processing.

Alternatively, a configuration in which a picture is divided into, forexample, tiles in accordance with the meaning of, for example, an objectin the image, and on the decoder side, only a partial region is decodedby selecting a tile to decode, is also acceptable. Moreover, by storingan attribute about the object (person, car, ball, etc.) and a positionof the object in the video (coordinates in identical images) asmetadata, the decoder side can identify the position of a desired objectbased on the metadata and determine which tile or tiles include thatobject. For example, as illustrated in FIG. 44 , metadata is storedusing a data storage structure different from pixel data such as an SEImessage in HEVC. This metadata indicates, for example, the position,size, or color of the main object.

Moreover, metadata may be stored in units of a plurality of pictures,such as stream, sequence, or random access units. With this, the decoderside can obtain, for example, the time at which a specific personappears in the video, and by fitting that with picture unit information,can identify a picture in which the object is present and the positionof the object in the picture.

Web Page Optimization

FIG. 45 illustrates an example of a display screen of a web page on, forexample, computer ex 111. FIG. 46 illustrates an example of a displayscreen of a web page on, for example, smartphone ex 115. As illustratedin FIG. 45 and FIG. 46 , a web page may include a plurality of imagelinks which are links to image content, and the appearance of the webpage differs depending on the device used to view the web page. When aplurality of image links are viewable on the screen, until the userexplicitly selects an image link, or until the image link is in theapproximate center of the screen or the entire image link fits in thescreen, the display apparatus (decoder) displays, as the image links,still images included in the content or I pictures, displays video suchas an animated gif using a plurality of still images or I pictures, forexample, or receives only the base layer and decodes and displays thevideo.

When an image link is selected by the user, the display apparatusdecodes giving the highest priority to the base layer. Note that ifthere is information in the HTML code of the web page indicating thatthe content is scalable, the display apparatus may decode up to theenhancement layer. Moreover, in order to guarantee real timereproduction, before a selection is made or when the bandwidth isseverely limited, the display apparatus can reduce delay between thepoint in time at which the leading picture is decoded and the point intime at which the decoded picture is displayed (that is, the delaybetween the start of the decoding of the content to the displaying ofthe content) by decoding and displaying only forward reference pictures(I picture, P picture, forward reference B picture). Moreover, thedisplay apparatus may purposely ignore the reference relationshipbetween pictures and coarsely decode all B and P pictures as forwardreference pictures, and then perform normal decoding as the number ofpictures received over time increases.

Autonomous Driving

When transmitting and receiving still image or video data such two- orthree-dimensional map information for autonomous driving or assisteddriving of an automobile, the reception terminal may receive, inaddition to image data belonging to one or more layers, information on,for example, the weather or road construction as metadata, and associatethe metadata with the image data upon decoding. Note that metadata maybe assigned per layer and, alternatively, may simply be multiplexed withthe image data.

In such a case, since the automobile, drone, airplane, etc., includingthe reception terminal is mobile, the reception terminal can seamlesslyreceive and decode while switching between base stations among basestations ex 106 through ex 110 by transmitting information indicatingthe position of the reception terminal upon reception request. Moreover,in accordance with the selection made by the user, the situation of theuser, or the bandwidth of the connection, the reception terminal candynamically select to what extent the metadata is received or to whatextent the map information, for example, is updated.

With this, in content providing system ex 100, the client can receive,decode, and reproduce, in real time, encoded information transmitted bythe user.

Streaming of Individual Content

In content providing system ex 100, in addition to high image quality,long content distributed by a video distribution entity, unicast ormulticast streaming of low image quality, short content from anindividual is also possible. Moreover, such content from individuals islikely to further increase in popularity. The server may first performediting processing on the content before the encoding processing inorder to refine the individual content. This may be achieved with, forexample, the following configuration.

In real-time while capturing video or image content or after the contenthas been captured and accumulated, the server performs recognitionprocessing based on the raw or encoded data, such as capture errorprocessing, scene search processing, meaning analysis, and/or objectdetection processing. Then, based on the result of the recognitionprocessing, the server—either when prompted or automatically—edits thecontent, examples of which include: correction such as focus and/ormotion blur correction; removing low-priority scenes such as scenes thatare low in brightness compared to other pictures or out of focus; objectedge adjustment; and color tone adjustment. The server encodes theedited data based on the result of the editing. It is known thatexcessively long videos tend to receive fewer views. Accordingly, inorder to keep the content within a specific length that scales with thelength of the original video, the server may, in addition to thelow-priority scenes described above, automatically clip out scenes withlow movement based on an image processing result. Alternatively, theserver may generate and encode a video digest based on a result of ananalysis of the meaning of a scene.

Note that there are instances in which individual content may includecontent that infringes a copyright, moral right, portrait rights, etc.Such an instance may lead to an unfavorable situation for the creator,such as when content is shared beyond the scope intended by the creator.Accordingly, before encoding, the server may, for example, edit imagesso as to blur faces of people in the periphery of the screen or blur theinside of a house, for example. Moreover, the server may be configuredto recognize the faces of people other than a registered person inimages to be encoded, and when such faces appear in an image, forexample, apply a mosaic filter to the face of the person. Alternatively,as pre- or post-processing for encoding, the user may specify, forcopyright reasons, a region of an image including a person or a regionof the background be processed, and the server may process the specifiedregion by, for example, replacing the region with a different image orblurring the region. If the region includes a person, the person may betracked in the moving picture the head region may be replaced withanother image as the person moves.

Moreover, since there is a demand for real-time viewing of contentproduced by individuals, which tends to be small in data size, thedecoder first receives the base layer as the highest priority andperforms decoding and reproduction, although this may differ dependingon bandwidth. When the content is reproduced two or more times, such aswhen the decoder receives the enhancement layer during decoding andreproduction of the base layer and loops the reproduction, the decodermay reproduce a high image quality video including the enhancementlayer. If the stream is encoded using such scalable encoding, the videomay be low quality when in an unselected state or at the start of thevideo, but it can offer an experience in which the image quality of thestream progressively increases in an intelligent manner. This is notlimited to just scalable encoding; the same experience can be offered byconfiguring a single stream from a low quality stream reproduced for thefirst time and a second stream encoded using the first stream as areference.

Other Usage Examples

The encoding and decoding may be performed by LSI ex 500, which istypically included in each terminal. LSI ex 500 may be configured of asingle chip or a plurality of chips. Software for encoding and decodingmoving pictures may be integrated into some type of a recording medium(such as a CD-ROM, a flexible disk, or a hard disk) that is readable by,for example, computer ex 111, and the encoding and decoding may beperformed using the software. Furthermore, when smartphone ex 115 isequipped with a camera, the video data obtained by the camera may betransmitted. In this case, the video data is coded by LSI ex 500included in smartphone ex 115.

Note that LSI ex 500 may be configured to download and activate anapplication. In such a case, the terminal first determines whether it iscompatible with the scheme used to encode the content or whether it iscapable of executing a specific service. When the terminal is notcompatible with the encoding scheme of the content or when the terminalis not capable of executing a specific service, the terminal firstdownloads a codec or application software then obtains and reproducesthe content.

Aside from the example of content providing system ex 100 that usesinternet ex 101, at least the moving picture encoder (image encoder) orthe moving picture decoder (image decoder) described in the aboveembodiments may be implemented in a digital broadcasting system. Thesame encoding processing and decoding processing may be applied totransmit and receive broadcast radio waves superimposed with multiplexedaudio and video data using, for example, a satellite, even though thisis geared toward multicast whereas unicast is easier with contentproviding system ex 100.

Hardware Configuration

FIG. 47 illustrates smartphone ex 115. FIG. 48 illustrates aconfiguration example of smartphone ex 115. Smartphone ex 115 includesantenna ex 450 for transmitting and receiving radio waves to and frombase station ex 110, camera ex 465 capable of capturing video and stillimages, and display ex 458 that displays decoded data, such as videocaptured by camera ex 465 and video received by antenna ex 450.Smartphone ex 115 further includes user interface ex 466 such as a touchpanel, audio output unit ex 457 such as a speaker for outputting speechor other audio, audio input unit ex 456 such as a microphone for audioinput, memory ex 467 capable of storing decoded data such as capturedvideo or still images, recorded audio, received video or still images,and mail, as well as decoded data, and slot ex 464 which is an interfacefor SIM ex 468 for authorizing access to a network and various data.Note that external memory may be used instead of memory ex 467.

Moreover, main controller ex 460 which comprehensively controls displayex 458 and user interface ex 466, power supply circuit ex 461, userinterface input controller ex 462, video signal processor ex 455, camerainterface ex 463, display controller ex 459, modulator/demodulator ex452, multiplexer/demultiplexer ex 453, audio signal processor ex 454,slot ex 464, and memory ex 467 are connected via bus ex 470.

When the user turns the power button of power supply circuit ex 461 on,smartphone ex 115 is powered on into an operable state by each componentbeing supplied with power from a battery pack.

Smartphone ex 115 performs processing for, for example, calling and datatransmission, based on control performed by main controller ex 460,which includes a CPU, ROM, and RAM. When making calls, an audio signalrecorded by audio input unit ex 456 is converted into a digital audiosignal by audio signal processor ex 454, and this is applied with spreadspectrum processing by modulator/demodulator ex 452 and digital-analogconversion and frequency conversion processing by transmitter/receiverex 451, and then transmitted via antenna ex 450. The received data isamplified, frequency converted, and analog-digital converted, inversespread spectrum processed by modulator/demodulator ex 452, convertedinto an analog audio signal by audio signal processor ex 454, and thenoutput from audio output unit ex 457. In data transmission mode, text,still-image, or video data is transmitted by main controller ex 460 viauser interface input controller ex 462 as a result of operation of, forexample, user interface ex 466 of the main body, and similartransmission and reception processing is performed. In data transmissionmode, when sending a video, still image, or video and audio, videosignal processor ex 455 compression encodes, via the moving pictureencoding method described in the above embodiments, a video signalstored in memory ex 467 or a video signal input from camera ex 465, andtransmits the encoded video data to multiplexer/demultiplexer ex 453.Moreover, audio signal processor ex 454 encodes an audio signal recordedby audio input unit ex 456 while camera ex 465 is capturing, forexample, a video or still image, and transmits the encoded audio data tomultiplexer/demultiplexer ex 453. Multiplexer/demultiplexer ex 453multiplexes the encoded video data and encoded audio data using apredetermined scheme, modulates and converts the data usingmodulator/demodulator (modulator/demodulator circuit) ex 452 andtransmitter/receiver ex 451, and transmits the result via antenna ex450.

When video appended in an email or a chat, or a video linked from a webpage, for example, is received, in order to decode the multiplexed datareceived via antenna ex 450, multiplexer/demultiplexer ex 453demultiplexes the multiplexed data to divide the multiplexed data into abitstream of video data and a bitstream of audio data, supplies theencoded video data to video signal processor ex 455 via synchronous busex 470, and supplies the encoded audio data to audio signal processor ex454 via synchronous bus ex 470. Video signal processor ex 455 decodesthe video signal using a moving picture decoding method corresponding tothe moving picture encoding method described in the above embodiments,and video or a still image included in the linked moving picture file isdisplayed on display ex 458 via display controller ex 459. Moreover,audio signal processor ex 454 decodes the audio signal and outputs audiofrom audio output unit ex 457. Note that since real-time streaming isbecoming more and more popular, there are instances in whichreproduction of the audio may be socially inappropriate depending on theuser’s environment. Accordingly, as an initial value, a configuration inwhich only video data is reproduced, i.e., the audio signal is notreproduced, is preferable. Audio may be synchronized and reproduced onlywhen an input, such as when the user clicks video data, is received.

Although smartphone ex 115 was used in the above example, threeimplementations are conceivable: a transceiver terminal including bothan encoder and a decoder; a transmitter terminal including only anencoder; and a receiver terminal including only a decoder. Further, inthe description of the digital broadcasting system, an example is givenin which multiplexed data obtained as a result of video data beingmultiplexed with, for example, audio data, is received or transmitted,but the multiplexed data may be video data multiplexed with data otherthan audio data, such as text data related to the video. Moreover, thevideo data itself rather than multiplexed data maybe received ortransmitted.

Although main controller ex 460 including a CPU is described ascontrolling the encoding or decoding processes, terminals often includeGPUs. Accordingly, a configuration is acceptable in which a large areais processed at once by making use of the performance ability of the GPUvia memory shared by the CPU and GPU or memory including an address thatis managed so as to allow common usage by the CPU and GPU. This makes itpossible to shorten encoding time, maintain the real-time nature of thestream, and reduce delay. In particular, processing relating to motionestimation, deblocking filtering, sample adaptive offset (SAO), andtransformation/quantization can be effectively carried out by the GPUinstead of the CPU in units of, for example pictures, all at once.

This aspect may be implemented in combination with one or more of theother aspects according to the present disclosure. In addition, part ofthe processes in the flowcharts, part of the constituent elements of theapparatuses, and part of the syntax described in this aspect may beimplemented in combination with other aspects.

INDUSTRIAL APPLICABILITY

The present disclosure is applicable to, for example, televisionreceivers, digital video recorders, car navigation systems, mobilephones, digital cameras, digital video cameras, video conferencesystems, and electron mirrors.

1-32. (canceled)
 33. A decoder which decodes a video, the decodercomprising: circuitry; and memory coupled to the circuitry, whereinusing the memory, the circuitry: obtains at least two items ofprediction information for a first partition included in the video;derives a template from a plurality of samples which neighbor the firstpartition; calculates at least two costs, using the template and the atleast two items of prediction information; using the at least two costs,(i) determines a first direction which is substantially perpendicular toa second direction in which a second partition is opposed to a thirdpartition in the first partition and (ii) assigns one of the at leasttwo items of prediction information to the second partition, and anotherof the at least two items of prediction information to the thirdpartition; and decodes the first partition according to the at least twoitems of prediction information.
 34. An encoder which encodes a video,the encoder comprising: circuitry; and memory coupled to the circuitry,wherein using the memory, the circuitry: obtains at least two items ofprediction information for a first partition included in the video;derives a template from a plurality of samples which neighbor the firstpartition; calculates at least two costs, using the template and the atleast two items of prediction information; using the at least two costs,(i) determines a first direction which is substantially perpendicular toa second direction in which a second partition is opposed to a thirdpartition in the first partition and (ii) assigns one of the at leasttwo items of prediction information to the second partition, and anotherof the at least two items of prediction information to the thirdpartition; and encodes the first partition according to the at least twoitems of prediction information.
 35. A decoding method for decoding avideo, the decoding method comprising: obtaining at least two items ofprediction information for a first partition included in the video;deriving a template from a plurality of samples which neighbor the firstpartition; calculating at least two costs, using the template and the atleast two items of prediction information; using the at least two costs,(i) determining a first direction which is substantially perpendicularto a second direction in which a second partition is opposed to a thirdpartition in the first partition and (ii) assigning one of the at leasttwo items of prediction information to the second partition, and anotherof the at least two items of prediction information to the thirdpartition; and decoding the first partition according to the at leasttwo items of prediction information.
 36. An encoding method for encodinga video, the encoding method comprising: obtaining at least two items ofprediction information for a first partition included in the video;deriving a template from a plurality of samples which neighbor the firstpartition; calculating at least two costs, using the template and the atleast two items of prediction information; using the at least two costs,(i) determining a first direction which is substantially perpendicularto a second direction in which a second partition is opposed to a thirdpartition in the first partition and (ii) assigning one of the at leasttwo items of prediction information to the second partition, and anotherof the at least two items of prediction information to the thirdpartition; and encoding the first partition according to the at leasttwo items of prediction information.